CN112401908A - Fatigue monitoring device, fatigue monitoring method, computing equipment and storage medium - Google Patents
Fatigue monitoring device, fatigue monitoring method, computing equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a fatigue monitoring device, comprising: the shell is made of flexible materials, and a through hole is formed in the first surface of the shell along the first direction; the FPC board is arranged inside the shell and provided with a micro control unit; the electroencephalogram acquisition electrode penetrates through the through hole and is arranged on the first surface, the electroencephalogram acquisition electrode is electrically connected with the micro control unit, and the electroencephalogram acquisition electrode is used for acquiring electroencephalogram signals of the forehead. By adopting the technical scheme, the fatigue monitoring device is convenient to use. The invention also discloses a fatigue monitoring method, a computing device and a storage medium.
Description
Technical Field
The invention relates to the technical field of biomedical engineering and mechanical electronic engineering, in particular to a fatigue monitoring device, a fatigue monitoring method, computing equipment and a storage medium.
Background
Fatigue has a great influence on the cognitive, emotional and behavioral abilities of the body. In wartime, when a pilot faces high load for a long time and has long voyage, the risk of brain fatigue of the pilot is increased, and battle casualties are easily caused. In daily life, a doctor can carry out a complex operation for dozens of hours, the doctor reports about accidents of sudden fatigue death frequently, and drivers are fatigued to cause traffic accidents. The fatigue state of the human body is judged through the human body spontaneous Electroencephalogram (EEG), does not depend on the subjective statement and active participation of the tested human body, and is currently determined as the gold standard of fatigue monitoring.
Therefore, the existing fatigue monitoring device mostly realizes fatigue judgment by acquiring electroencephalogram signals. Because the electroencephalogram signal is a very weak signal, the amplitude of the spontaneous electroencephalogram is about 5-200uV, and the electroencephalogram signal is particularly easily interfered by environmental electromagnetic interference and the movement of a tested person, the conventional fatigue monitoring device is mostly connected with a naked electroencephalogram collecting electrode through a long connecting wire through data analysis equipment, the electroencephalogram collecting electrode is placed at a corresponding position to collect the electroencephalogram signal after scalp cleaning treatment is carried out on the tested person, conductive paste is added into the electrode and the like, the monitoring process is always kept still as much as possible, so that the situation that the electroencephalogram collecting electrode is separated from the standard collecting position by the movement of the connecting wire and the like is avoided, and the monitoring device is only often applied to the experimental environment and the tested controllable places of hospitals and scientific research institutions.
Disclosure of Invention
The applicant has found that the existing fatigue monitoring devices suffer from a complex use. The applicant further researches and discovers that the whole device is large in size and complex to operate due to the fact that the existing fatigue monitoring device is usually connected with data analysis equipment and a naked collecting electrode through long connecting wires to collect electroencephalogram signals.
The invention aims to solve the problem that the fatigue monitoring device in the prior art is complex to use.
In order to solve the above technical problem, an embodiment of the present invention discloses a fatigue monitoring device, including: the shell is made of flexible materials, and a through hole is formed in the first surface of the shell along the first direction; the FPC board is arranged inside the shell and provided with a micro control unit; the electroencephalogram acquisition electrode penetrates through the through hole and is arranged on the first surface, the electroencephalogram acquisition electrode is electrically connected with the micro control unit, and the electroencephalogram acquisition electrode is used for acquiring electroencephalogram signals of the forehead; the first ear clip comprises first magnetic suction parts which are symmetrically arranged, a bias acquisition electrode and a reference acquisition electrode are arranged on the first magnetic suction parts, and the bias acquisition electrode and the reference acquisition electrode are electrically connected with the micro control unit; second ear clamp and second connecting portion, second ear clamp and casing are connected to the second connecting portion, and first connecting portion and second connecting portion symmetry set up in the casing along the both ends of second direction, and the second ear clamp is including the second magnetism portion of inhaling that the symmetry set up, and the second magnetism is inhaled and is provided with blood oxygen collector in the portion, and blood oxygen collector is connected with little the control unit electricity, and little the control unit is inhaled a portion electricity with the second magnetism and is connected.
By adopting the technical scheme, the fatigue monitoring device is convenient to use.
Optionally, the first ear clip, and/or the second ear clip, includes symmetrically disposed curved portions, the curved portions connecting the first magnetic attraction portion and the first connection portion, and/or connecting the second magnetic attraction portion and the second connection portion.
Optionally, the number of the electroencephalogram acquisition electrodes is multiple, the number of the through holes is the same as that of the electroencephalogram acquisition electrodes, the electroencephalogram acquisition electrodes are arranged at intervals along the second direction, and the distance between the electroencephalogram acquisition electrodes located at the two ends along the second direction is 60-100 mm.
Optionally, the fatigue monitoring device further comprises a strap, strap holes are formed in two ends of the shell along the second direction, and the strap penetrates through the strap holes to be connected with the shell.
Optionally, the fatigue monitoring device further comprises a key portion, the key portion is concavely arranged on the second surface of the shell along the first direction, and the key portion is electrically connected with the micro control unit.
Optionally, the fatigue monitoring device further comprises a status light, the status light is disposed on the second surface, and the status light is electrically connected with the micro control unit.
Optionally, fatigue monitoring devices still includes the power and inhales the formula USB interface with magnetism, and the power sets up in the casing, and the power is connected with little the control unit and magnetism and is inhaled formula USB interface electricity, inhales the formula USB interface concave second face of locating.
Optionally, a wireless transmission unit is further arranged on the FPC board, and the wireless transmission unit is electrically connected with the micro control unit.
Optionally, the fatigue monitoring device further comprises a microphone, the microphone is arranged on the shell and electrically connected with the micro control unit, and the microphone is used for collecting sound signals.
Optionally, the fatigue monitoring device further comprises a speaker, the speaker is arranged on the housing, the speaker is electrically connected with the micro control unit, and the speaker is used for outputting a voice prompt.
Optionally, the micro control unit includes an active electrode conversion unit, a multistage filtering amplification unit, an analog-to-digital conversion unit and a microprocessor, which are electrically connected in sequence, and the active electrode conversion unit is electrically connected with the electroencephalogram acquisition electrode.
The embodiment of the invention also discloses a fatigue monitoring method, which comprises the following steps: acquiring first electroencephalogram data and first blood oxygen data; processing the first electroencephalogram data and the first blood oxygen data respectively to obtain an electroencephalogram characteristic and a blood oxygen characteristic; and inputting the electroencephalogram characteristic and the blood oxygen characteristic into a classifier for fatigue judgment.
Optionally, before the step of processing the first electroencephalogram data and the first blood oxygen data to obtain an electroencephalogram characteristic and a blood oxygen characteristic, the method further includes the following steps: acquiring pre-sampled second electroencephalogram data; inputting the second electroencephalogram data into an identity recognition model for identity recognition; and if the identity recognition fails, storing the second electroencephalogram data.
Optionally, the identity recognition model is trained using a convolutional neural network.
Optionally, the fatigue monitoring method further comprises the steps of: and training and updating the identity recognition model according to the second electroencephalogram data.
Optionally, the step of inputting the electroencephalogram feature and the blood oxygen feature into a classifier for fatigue judgment includes: if the identity identification is successful, inputting the electroencephalogram feature and the blood oxygen feature into a specific classifier corresponding to the identified identity information for fatigue judgment; and if the identity recognition fails, inputting the electroencephalogram characteristic and the blood oxygen characteristic into a general classifier for fatigue judgment.
Optionally, the electroencephalogram feature comprises a functional connectivity feature, a nonlinear dynamics feature, a power spectrum feature, and the blood oxygen feature comprises a blood oxygen saturation variability feature.
Optionally, the functional connection characteristic is mutual information values corresponding to theta waves, alpha waves, beta waves and gamma waves in the first electroencephalogram data, the nonlinear dynamics characteristic is approximate entropies corresponding to the theta waves, the alpha waves, the beta waves and the gamma waves, and the power spectrum characteristic is a power ratio corresponding to the theta waves, the alpha waves, the beta waves and the gamma waves.
Optionally, the fatigue monitoring method further comprises the steps of: obtaining pre-sampled second blood oxygen data, and calculating to obtain an average value P of the blood oxygen saturation in the second blood oxygen dataref(ii) a Calculating to obtain a blood oxygen saturation variability characteristic of (P/P) according to the blood oxygen saturation value P of the first blood oxygen dataref)4。
Optionally, the variability of blood oxygen saturation is characterized by (P/P) in the calculationref)4Before the step (2), further comprising the steps of: the first blood oxygen data and the second blood oxygen data are processed to remove outliers less than 85.
Optionally, the fatigue monitoring method further comprises the steps of: if the fatigue is judged, the electric stimulation is output.
Optionally, the fatigue monitoring method further comprises the steps of: if the fatigue is judged, a voice prompt is played.
Optionally, the fatigue monitoring method further comprises the steps of: if the identity recognition fails and the fatigue is judged, storing the first electroencephalogram data; and training and generating a corresponding classifier according to the first electroencephalogram data and the second electroencephalogram data.
The embodiment of the invention also discloses a computing device, which comprises: a processor adapted to implement various instructions; a memory adapted to store a plurality of instructions, the instructions adapted to be loaded by the processor and to perform any of the fatigue monitoring methods described above.
The embodiment of the invention also discloses a storage medium, wherein a plurality of instructions are stored in the storage medium, and the instructions are suitable for being loaded by a processor and executing any one of the fatigue monitoring methods.
Drawings
FIG. 1 illustrates a rear view of a fatigue monitoring device in an embodiment of the present invention;
FIG. 2 shows a top view of a fatigue monitoring device in accordance with a further embodiment of the present invention;
FIG. 3 shows a front view of a fatigue monitoring device in another embodiment of the present invention;
FIG. 4 shows a schematic block diagram of the connection of a micro control unit in a further embodiment of the invention;
FIG. 5 is a flow chart illustrating the steps of a fatigue monitoring method in one embodiment of the present invention;
fig. 6 shows a flow chart of the steps of a fatigue monitoring method in a further embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure. While the invention will be described in conjunction with the preferred embodiments, it is not intended that features of the invention be limited to these embodiments. On the contrary, the invention is described in connection with the embodiments for the purpose of covering alternatives or modifications that may be extended based on the claims of the present invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be practiced without these particulars. Moreover, some of the specific details have been left out of the description in order to avoid obscuring or obscuring the focus of the present invention. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
It should be noted that in this specification, like reference numerals and letters refer to like items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.
In the description of the embodiments of the present invention, it should be noted that the terms "upper", "lower", "inner", "bottom", and the like refer to orientations or positional relationships based on those shown in the drawings or orientations or positional relationships that are conventionally arranged when the products of the present invention are used, and are used for convenience in describing the present invention and simplifying the description, but do not refer to or imply that the devices or elements referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
The terms "first," "second," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Referring to fig. 1 and 2, an embodiment of the present invention provides a fatigue monitoring apparatus including: the shell comprises a shell body 1, wherein the shell body 1 is made of a flexible material, and a through hole 12 is formed in a first surface 11 of the shell body 1 along a first direction (the X direction is shown in figure 2); the FPC board 2 is arranged inside the shell 1, and a micro control unit 21 is arranged on the FPC board 2; the electroencephalogram acquisition electrode 3 penetrates through the through hole 12 and is arranged on the first surface 11, the electroencephalogram acquisition electrode 3 is electrically connected with the micro control unit 21, and the electroencephalogram acquisition electrode 3 is used for acquiring an electroencephalogram signal of the forehead; the first ear clip 4 and the first connecting part 5, the first connecting part 5 is connected with the first ear clip 4 and the housing 1, the first ear clip 4 comprises first magnetic attracting parts 41 which are symmetrically arranged, a bias collecting electrode (not shown) and a reference collecting electrode (not shown) are arranged on the first magnetic attracting part 41, and the bias collecting electrode and the reference collecting electrode are electrically connected with the micro control unit 21; the second ear clip 6 and the second connecting portion 7, the second connecting portion 7 connects the second ear clip 6 and the housing 1, the first connecting portion 5 and the second connecting portion 7 are symmetrically arranged at two ends of the housing 1 along a second direction (shown as Y direction in fig. 1), the second ear clip 6 comprises second magnetic attracting portions 61 which are symmetrically arranged, a blood oxygen collector (not shown) is arranged on the second magnetic attracting portion 61, and the blood oxygen collector is electrically connected with the micro control unit 21; the micro control unit 21 is electrically connected to the second magnetic attraction part 61.
In this embodiment, the casing 1 is made of a flexible material such as silica gel or rubber, and the first surface 11 of the casing 1 along the first direction is provided with a through hole 12, that is, the through hole 12 penetrates through the first surface 11 to the inside of the casing 1, but does not penetrate through the whole casing 1, and the through hole 12 is used for the electroencephalogram acquisition electrode 3 to penetrate through. Be provided with FPC board 2 in the casing 1, Flexible Printed Circuit board (Flexible Printed Circuit) promptly is provided with microcontrol unit 21 on the FPC, and microcontrol unit 21 is connected with brain electricity collection electrode 3 electricity to can handle the brain electrical signal who gathers. The brain electricity collecting electrode 3 passes through the through hole 12 and is arranged on the first surface 11 of the shell 1, and the brain electricity collecting electrode 3 is used for collecting brain electricity signals of the forehead.
By adopting the technical scheme, the fatigue monitoring device is convenient to use. The fatigue monitoring device disclosed by the embodiment directly sets the electroencephalogram acquisition electrode 3 on the surface of the shell 1, carries out signal processing by the micro control unit 21 arranged in the shell 1, is different from the electroencephalogram acquisition electrode which is connected with a data analysis device and is exposed without the shell through a long connecting wire in the prior art, is miniaturized, is convenient to carry and use, and is wider in use scene. When in use, the shell 1 is only required to be placed at a corresponding monitoring position for monitoring. And the micro control unit 21 is arranged in the shell 1, and a long connecting wire is not needed when the micro control unit 21 is electrically connected with the electroencephalogram acquisition electrode 3, so that the electroencephalogram signal acquisition is more stable and reliable. Simultaneously, because casing and circuit board among this embodiment are flexible material, in the use, can laminate user's forehead well according to the flexible deformation of shape adaptability of user's forehead, change in fixedly, further promoted the accuracy of the electroencephalogram signal who gathers. In addition, compared with a common PCB, the FPC board is adopted, the maximum area of the circuit board can be increased in the limited flexible shell space, and the whole device can be more miniaturized by the FPC board under the condition of the same number of circuit devices. In the same flexible shell space, more circuit devices than the PCB can be placed on the FPC board, so that the function of the device is expanded conveniently. And the FPC board is thinner, so the thickness and the weight of the device are reduced, and the wearing comfort is enhanced. Preferably, casing 1 is silica gel, is convenient for vulcanize the encapsulation FPC through low temperature silica gel, guarantees that circuit element does not receive high temperature to damage to make casing 1 possess better toughness, promote the travelling comfort when production efficiency, yield and use. Preferably, one end of the electroencephalogram acquisition electrode 3 is fixedly arranged on the FPC board 2, and the other end of the electroencephalogram acquisition electrode penetrates through the through hole 12 and is fixedly arranged on the first surface 11, so that the size is further reduced, and the stability of acquired signals is improved.
In this embodiment, through the first ear clip 4 of formula of magnetism, can fix the bias collecting electrode and reference collecting electrode reliably and steadily at the ear through magnet, the signal of telecommunication of gathering is more stable. Gather electrode and reference with the biasing and gather electrode setting and inhale 41 portions of magnetism that can make when wearing more comfortable at the first magnetism of symmetry formula, and guarantee that electrode and ear are more stable to be contacted, and the ear is nearer from the forehead, can make 5 length of first connecting portion shorter, convenient to use. In one embodiment, the first magnetic attraction 41 fixes the bias and reference collection electrodes by sintering the dry electrode with a magnet pack. Preferably, the first connecting portion 5 is a shielding wire wrapped by silica gel, so that the electrical stability of the acquired electrical signal is improved. Preferably, the first connecting portion 5 is connected to the upper portion of the housing 1 during use, so as to avoid interference with the user's sight during use, and is suitable for various application scenarios.
In this embodiment, through setting up blood oxygen collector on the second magnetism of symmetry portion 61 is inhaled, can gather user's blood oxygen data steadily, carries out fatigue monitoring and evaluation through blood oxygen data and brain electrical data are synthesized, and the fatigue monitoring result that obtains is more accurate. The blood oxygen collector is arranged on the ear clip different from the bias collecting electrode and the reference collecting electrode, so that the interference between circuits can be avoided, and the reliability and the accuracy of signal collection are improved. The blood oxygen collector may be a blood oxygen saturation sensor, or may be a transmission type photodiode and an LED light emitting diode which are symmetrically disposed, which is not limited in this embodiment. Through electrically connecting micro control unit 21 and second magnetism portion 61 for magnetism portion not only can play the fixed action, more can regard magnet as stimulating electrode to use. The complexity of the design of the stimulation portion can be effectively reduced, and thus the housing 1 can be designed to be very small. When the fatigue monitoring result is fatigue, the micro control unit 21 sends an electric signal to the second magnetic attraction part 61 for electro-acupuncture stimulation, so that the structure is simple, the fatigue intervention is timely and reliably completed, and safety accidents caused by fatigue of users are avoided. Through the second magnetism portion 61 output electro photoluminescence of inhaling, can avoid inhaling the interference that the electrode gathered analog signal on the portion 41 to first magnetism, promote signal acquisition's accuracy.
Referring to fig. 3, in another embodiment of the invention, a fatigue monitoring device is provided, wherein the first ear clip 4 and/or the second ear clip 6 comprise symmetrically arranged bent portions 8, and the bent portions 8 connect the first magnetic attraction portion 41 and the first connecting portion 5 and/or connect the second magnetic attraction portion 61 and the second connecting portion 7. All outwards bend through setting up symmetrical flexion 8, can make the profile of ear of adaptation that the ear clip is better when using, the ear edge can be held to flexion 8, is convenient for adjust the pinch point degree of depth and the position of ear clip.
Referring to fig. 1, another embodiment of the invention provides a fatigue monitoring device, the number of the electroencephalogram acquisition electrodes 3 is multiple, the number of the through holes 12 is the same as that of the electroencephalogram acquisition electrodes 3, the multiple electroencephalogram acquisition electrodes 3 are arranged at intervals along the second direction, and the distance between the electroencephalogram acquisition electrodes 3 positioned at two ends along the second direction is 60mm-100 mm. The electroencephalogram signals of multiple parts of the forehead can be acquired by arranging the multiple electroencephalogram acquisition electrodes 3, and the accuracy of a fatigue monitoring result is improved. Meanwhile, the distance between the electroencephalogram acquisition electrodes 3 at the two ends is 60-100 mm, so that the applicant finds that the corresponding shell 1 at the distance can adapt to the forehead of most people through a large number of experiments, can acquire the corresponding electroencephalogram signals more accurately, can improve the reliability of the device, and avoids overlong easy bending damage. Preferably, the number of the electroencephalogram acquisition electrodes 3 is three, so that the accuracy of a monitoring result can be ensured, and the processing load of the micro control unit 21 is reduced. Preferably, be provided with the recess on the casing 1 between the brain electricity collection electrode 3, improve the outward appearance on the one hand, on the other hand can reduce the area of contact of casing and skin, and is more ventilative, reduces the user and perspires.
Referring to fig. 3, another embodiment of the present invention provides a fatigue monitoring device, further comprising a strap (not shown), wherein strap holes 13 are provided at both ends of the housing 1 in the second direction (Y direction shown in fig. 3), and the strap is connected to the housing 1 through the strap holes 13. This embodiment is through setting up the bandage, can fix casing 1 at user's forehead more reliably and stablely, is convenient for use under the more frequent scene of user's activity such as driving.
Referring to fig. 2 and 3, another embodiment of the present invention provides a fatigue monitoring device, further comprising a key portion 15, wherein the key portion 15 is recessed on the second surface 14 of the housing 1 along a first direction (X direction shown in fig. 2), and the key portion 15 is electrically connected to the micro control unit 21. The button part 15 is arranged on the second surface 14 back to the electroencephalogram acquisition electrode 3, so that the operation of a user in the using process is facilitated. The recessed arrangement, i.e. the key portion 15 is lower than the surrounding plane of the housing 1, can be used to avoid the fatigue monitoring device from being erroneously operated by a user when the user wears the device or sleeps.
Referring to fig. 3, another embodiment of the present invention provides a fatigue monitoring device, further comprising a status light 16, wherein the status light 16 is disposed on the second side 14, and the status light 16 is electrically connected to the micro control unit 21. The status light 16 carries out the light suggestion according to the operating condition of device, promotes the convenience of using.
Referring to fig. 3, another embodiment of the present invention provides a fatigue monitoring device, further including a power supply (not shown) and a magnetic USB interface 17, wherein the power supply is disposed in the housing 1, the power supply is electrically connected to the micro control unit 21 and the magnetic USB interface 17, and the magnetic USB interface 17 is recessed in the second surface 14. In the embodiment, the fatigue monitoring device is internally provided with a power supply which can be a button cell or the like, does not need to be externally connected and is convenient for daily use. Magnetism is inhaled formula USB interface 17 through setting up and can be convenient for charge to the power, compares in plug-in interface, can reduce the volume of device, and is convenient for carry out water repellent to the interface, and the concave mistake of establishing can avoiding is touched. Preferably, the fatigue monitoring device further comprises a storage unit (not shown) for storing the acquired electroencephalogram data, and the data stored in the storage unit can be transmitted through the magnetic USB interface 17, so that the acquisition, analysis and processing of a large amount of data are facilitated.
In another embodiment of the present invention, a wireless transmission unit (not shown) is further disposed on the FPC board 2, and the wireless transmission unit is electrically connected to the micro control unit 21. In this embodiment, wireless transmission unit is used for the computer data wireless transmission who will gather to mobile terminal, high in the clouds server etc. is convenient for carry out a large amount of data analysis and processing, and the concrete mode of transmission can be WIFI, ZIGBEE, classic bluetooth and BLE (bluetooth low energy consumption). Preferably, the wireless transmission unit transmits data through BLE, and is suitable for being applied to a long-term monitoring application scenario, and the power consumption is smaller.
Referring to fig. 1 and 3, another embodiment of the present invention provides a fatigue monitoring device, further comprising a microphone 18, wherein the microphone 18 is disposed on the housing 1, the microphone 18 is electrically connected to the micro control unit 21, and the microphone 18 is used for collecting sound signals. In the present embodiment, the microphone 18 is provided to collect the sound signal, and the micro control unit 21 analyzes the sound signal to find out abnormality such as snoring and whistling in time, thereby further improving the safety during use. Preferably, the microphone 18 is provided with a waterproof breathable film, so that water stain is prevented from entering in the using process, and the stability is improved.
Referring to fig. 1 and 3, in another embodiment of the present invention, a fatigue monitoring device is provided, which further includes a speaker 19, the speaker 19 is disposed on the housing 1, the speaker 19 is electrically connected to the micro control unit 21, and the speaker 19 is configured to output a voice prompt. This embodiment, through setting up speaker 19, when fatigue monitoring result is tired, can in time output voice prompt, remind the user, promote to use and experience.
Referring to fig. 4, in another embodiment of the present invention, a fatigue monitoring device is provided, where the micro control unit 21 includes an active electrode conversion unit 211, a multi-stage filtering amplification unit 212, an analog-to-digital conversion unit 213 and a microprocessor 214, which are electrically connected in sequence, and the active electrode conversion unit 211 is electrically connected to the electroencephalogram acquisition electrode 3. In the embodiment, the active electrode conversion unit 211 and the multistage filtering amplification unit 212 are arranged, so that a weak electric signal can be amplified, environmental interference is avoided, and because the electroencephalogram signals on the forehead are acquired by the fatigue monitoring device, the electroencephalogram acquisition electrode 3 can adopt a gel electrode, a silver chloride sintered dry electrode or an electrocardio patch and the like, scalp cleaning treatment and conductive paste adding are not needed during use, and the electroencephalogram acquisition electrode can be directly measured and can be used for rapid monitoring of electroencephalogram. In one embodiment, the active electrode switching unit 211 uses an operational amplifier as a voltage follower for level keeping, provides a larger input impedance, and reduces interference to the collected electrical signal. Preferably, the active electrode converting unit 211 employs an input impedance of 50M Ω or more. At this time, even if the user moves to cause the collection electrode to move, the contact resistance change generated when the collection electrode moves is hundreds of ohms, and the impedance relative to 50M Ω ohms can be ignored, so the requirement of the equipment on the user is very low, and the application scene is wider. Preferably, the multistage filtering and amplifying unit 212 mainly comprises an instrument amplifying circuit and a band-pass filtering circuit, wherein the intermediate signal amplified by the instrument is output to the bias collecting electrode in a reversed phase manner through the bias circuit, and is similar to a right leg driving circuit for electrocardio collection. On one hand, the method is used for eliminating power frequency common mode interference, and on the other hand, the method is used for biasing the original signal to be close to the 0 point position, and is beneficial to amplification and filtering of subsequent signals.
Referring to fig. 5, an embodiment of the present invention provides a fatigue monitoring method, including the following steps: s1: acquiring first electroencephalogram data and first blood oxygen data; s2: processing the first electroencephalogram data and the first blood oxygen data respectively to obtain an electroencephalogram characteristic and a blood oxygen characteristic; s3: and inputting the electroencephalogram characteristic and the blood oxygen characteristic into a classifier for fatigue judgment.
In the embodiment, the electroencephalogram data and the blood oxygen data are input into the classifier together for fatigue judgment, and compared with the judgment and analysis of single dimensionality only by using the electroencephalogram data or the blood oxygen data, the accuracy of a fatigue judgment result can be improved, and the misjudgment is reduced. The device for collecting the electroencephalogram data and the blood oxygen data can be selected correspondingly according to needs, a plurality of devices can be used for collecting the electroencephalogram data and the blood oxygen data respectively, the same device can also be used for collecting the electroencephalogram data and the blood oxygen data, the structure of the device can be selected according to needs, and the implementation mode does not limit the structure. In an embodiment, the fatigue monitoring method uses the fatigue monitoring device in any one of the foregoing embodiments to collect electroencephalogram data and blood oxygen data, and performs fatigue judgment through the micro control unit 21, or may send the data to a mobile terminal, a cloud server, and the like to perform fatigue judgment. In other embodiments, other structures of the device may be used for acquiring electroencephalogram data and blood oxygen data. The classifier may be a vector machine classifier or the like, and this embodiment does not limit this.
Before the step S2 of processing the first electroencephalogram data and the first blood oxygen data to obtain an electroencephalogram characteristic and a blood oxygen characteristic, respectively, the method further includes the following steps: acquiring pre-sampled second electroencephalogram data; inputting the second electroencephalogram data into an identity recognition model for identity recognition; and if the identity recognition fails, storing the second electroencephalogram data.
In this embodiment, the second electroencephalogram data may be acquired simultaneously with the first electroencephalogram data, or may be acquired separately, and the order of the separate acquisition is not limited in this embodiment. By carrying out identity recognition, different subsequent processing can be conveniently carried out according to whether a user is an existing person in the identity model, if the recognition fails, corresponding second electroencephalogram data are stored, the model can be conveniently optimized subsequently, and the reliability and the accuracy of the fatigue monitoring method are improved. In one embodiment, 300 pieces of electroencephalogram data of a user are collected and input into the identity recognition model, when the recognition matching rate is lower than 90%, the recognition is judged to be failed, and the recognition accuracy rate of the identity model is higher. In a preferred embodiment, the fatigue monitoring method uses any one of the fatigue monitoring devices in the aforementioned embodiments to collect electroencephalogram data and blood oxygen data, and the fatigue monitoring device includes a communication unit, and sends the collected data to a cloud server in a wired or wireless manner, and the cloud server completes identification and fatigue judgment. The cloud server can store more identity models, the operation efficiency is higher, and the universality of the fatigue monitoring method is improved. In other embodiments, other structures of the device may be used for acquiring electroencephalogram data and blood oxygen data.
In another embodiment of the invention, a fatigue monitoring method is provided, wherein the identity recognition model is obtained by training a convolutional neural network. In the embodiment, the convolutional neural network is used for training the identity recognition model, so that the recognition accuracy of the identity recognition model can be improved. Preferably, the convolutional neural network is added with an inception network structure, so that the accuracy of the identity recognition model is improved. In one embodiment, 300 pieces of electroencephalogram data of a user in a non-fatigue state are collected for training an identity recognition model, for example, the sampling frequency is 5 minutes, and the sampling frequency is 60 times/minute.
Another embodiment of the present invention provides a fatigue monitoring method, further comprising the steps of: and training and updating the identity recognition model according to the second electroencephalogram data. In the embodiment, the identity recognition model is updated through the second electroencephalogram data, so that the operation efficiency can be improved when the second electroencephalogram data are reused. In this embodiment, the device for acquiring electroencephalogram data and blood oxygen data can be selected accordingly, which is not limited in this embodiment. Preferably, the updating of the identity recognition model is performed by using a deep learning model, such as a convolutional neural network, so that the updating efficiency can be improved.
Another embodiment of the present invention provides a fatigue monitoring method, wherein the step of inputting the electroencephalogram characteristic and the blood oxygen characteristic into a classifier for fatigue determination S3 includes: if the identity identification is successful, inputting the electroencephalogram feature and the blood oxygen feature into a specific classifier corresponding to the identified identity information for fatigue judgment; and if the identity recognition fails, inputting the electroencephalogram characteristic and the blood oxygen characteristic into a general classifier for fatigue judgment. In the embodiment, by using the method that one fatigue classifier is used by one user and a universal fatigue classifier is used by a new user, the problem of low fatigue classification accuracy caused by individual difference can be effectively solved, and the accuracy of fatigue judgment is improved.
The invention further provides a fatigue monitoring method, wherein the electroencephalogram characteristics comprise a functional connection characteristic, a nonlinear dynamics characteristic and a power spectrum characteristic, and the blood oxygen characteristics comprise a blood oxygen saturation variability characteristic. In the embodiment, the electroencephalogram data are processed and analyzed from three different dimensions by determining the electroencephalogram characteristics as the functional connection characteristics, the nonlinear dynamics characteristics and the power spectrum characteristics, so that the accuracy of fatigue judgment can be further improved. The functional connection characteristic, the nonlinear dynamics characteristic and the power spectrum characteristic can be obtained based on one or more of theta wave, alpha wave, beta wave and gamma wave corresponding to the acquired electroencephalogram data, and the blood oxygen saturation variability characteristic is mainly used for evaluating whether the blood oxygen saturation is abnormal or not, and can be used for evaluating whether the blood oxygen saturation exceeds a normal value or not.
The invention further provides a fatigue monitoring method, which is characterized in that the functional connection characteristic is mutual information values corresponding to theta waves, alpha waves, beta waves and gamma waves in the first electroencephalogram data, the nonlinear dynamics characteristic is approximate entropies corresponding to the theta waves, the alpha waves, the beta waves and the gamma waves, and the power spectrum characteristic is a power ratio corresponding to the theta waves, the alpha waves, the beta waves and the gamma waves. In this embodiment, through a large number of experimental studies, the applicant finds that mutual information values corresponding to the theta wave, the alpha wave, the beta wave, and the gamma wave in the first electroencephalogram data serve as functional connection characteristics, approximate entropies corresponding to the theta wave, the alpha wave, the beta wave, and the gamma wave serve as nonlinear dynamics characteristics, and power ratios corresponding to the theta wave, the alpha wave, the beta wave, and the gamma wave serve as power spectrum characteristics, so that not only can the accuracy of fatigue judgment be ensured, but also the computational load is reduced. Preferably, the power spectrum feature comprises Ealpha/Ebeta、(Ealpha+Etheta)/Ebeta、(Ealpha+Etheta)/(Ebeta+Egamma)、Etheta/EbetaAnd the accuracy of the operation is further improved.
In one embodiment, a 90-minute simulated driving task is adopted to induce driving fatigue and collect 24-lead electroencephalogram signals of human electroencephalogram, electroencephalogram data at the beginning of an experiment are selected as input data of identity recognition, and a convolutional neural network model is utilized to obtain an average identity recognition accuracy rate of 98.5% (96.3% -100%) in 31 subjects. The sampling frequency of the electroencephalogram data is 60 times/min, and the lowest reaction time and the highest reaction time in the experimental process are selectedThe corresponding 5-minute electroencephalogram signals are used as electroencephalogram data in a waking state and a fatigue state. Preprocessing the electroencephalogram data, wherein the preprocessing refers to carrying out threshold value drying removal, baseline drift removal, 4-40Hz filtering and the like on the acquired electroencephalogram signals. The applicant finds through a large number of experiments that 4-40Hz filtering can keep electroencephalogram signals of most people, filter out clutter and reduce interference. Calculating electroencephalogram characteristics, such as functional connection characteristics, of the preprocessed electroencephalogram data, wherein the characteristics can be 4 characteristics of mutual information values corresponding to theta waves, alpha waves, beta waves and gamma waves; for example, the nonlinear dynamics characteristics can be approximate entropies corresponding to theta waves, alpha waves, beta waves and gamma waves, and the approximate entropies are 8 characteristics in total; e.g. power spectral characteristics, may be Ealpha/Ebeta、(Ealpha+Etheta)/Ebeta、(Ealpha+Etheta)/(Ebeta+Egamma)、Etheta/EbetaAnd the two leaders have 8 characteristics. In one embodiment, 20 features are selected by a recursive feature elimination-support vector machine feature selection algorithm and then used as input of a support vector machine classifier to calculate the driving fatigue classification accuracy, the accuracy in the samples of the top three lead pairs is 83.2%, 83.0% and 82.4% respectively, and the positions are located in forehead non-hair coverage areas; the electroencephalogram characteristics extracted from the 3 leads of the non-hair coverage area are used as the input of the convolutional neural network again for classification, the accuracy of 96.0% is obtained in a sample, and the accuracy of 82.1% is obtained in a non-sample interval. Preferably, the fatigue monitoring method adopts the fatigue monitoring device in any one of the foregoing embodiments to acquire electroencephalogram data and blood oxygen data, and the first surface 11 of the housing 1 of the fatigue monitoring device is sequentially provided with three electroencephalogram acquisition electrodes 3 for acquiring electroencephalogram data corresponding to three leads in a non-hair area on the front side of the forehead of a user. The distance between the brain electricity collecting electrodes 3 on the two sides is 60mm-100mm, and brain electricity signals at FP1 and FP2 on the forehead of different people can be accurately collected. The fatigue judgment accuracy rate can reach 96.0% by singly collecting electroencephalogram data through the fatigue monitoring device, and the accuracy of fatigue judgment can be further improved by combining blood oxygen data.
In yet another embodiment of the present invention providesA method of fatigue monitoring, further comprising the steps of: obtaining pre-sampled second blood oxygen data, and calculating to obtain an average value P of the blood oxygen saturation in the second blood oxygen dataref(ii) a Calculating to obtain a blood oxygen saturation variability characteristic of (P/P) according to the blood oxygen saturation value P of the first blood oxygen dataref)4. In the present embodiment, the applicant found through a large number of experiments that (P/P) is set based on the average value of the normal blood oxygen saturation at the time of preliminary samplingref)4As the blood oxygen saturation variability feature, whether blood oxygen is normal or not can be well judged, and the accuracy of fatigue judgment can be greatly improved after the blood oxygen saturation variability feature is combined with the electroencephalogram feature. The amount of the blood oxygen saturation values included in the second blood oxygen data may be adaptively adjusted according to the calculation capability, which is not limited in this embodiment. In one embodiment, the sampling frequency of the blood oxygen data is consistent with the sampling frequency of the electroencephalogram data, and 300 blood oxygen saturation monitoring values are acquired as the second blood oxygen data.
Another embodiment of the invention provides a fatigue monitoring method, wherein the calculation result shows that the blood oxygen saturation degree variability characteristic is (P/P)ref)4Before the step (2), further comprising the steps of: the first blood oxygen data and the second blood oxygen data are processed to remove outliers less than 85. In the embodiment, the blood oxygen saturation value which is obviously abnormal is removed, so that the misjudgment can be avoided.
Referring to fig. 6, another embodiment of the present invention provides a fatigue monitoring method, further including the steps of: s4: if the fatigue is judged, the electric stimulation is output. In this embodiment, can carry out fatigue early warning and intervention better through the electro photoluminescence user, and the electro photoluminescence compares in modes such as light warning, and is more direct effective, and avoids the lamp line to change the interference under the application scenes such as driving. In an embodiment, the fatigue monitoring method may adopt the fatigue monitoring device in any one of the foregoing embodiments to perform data acquisition, as shown in fig. 3, at this time, the second magnetic attraction part 61 may directly output electrical stimulation, and no additional stimulation structure is required, so that the structure of the fatigue monitoring device is simplified, and the realization of fatigue early warning and intervention is facilitated.
Another embodiment of the present invention provides a fatigue monitoring method, further comprising the steps of: if the fatigue is judged, a voice prompt is played. In the embodiment, the fatigue early warning and intervention can be timely and effectively finished through voice reminding.
Another embodiment of the present invention provides a fatigue monitoring method, further comprising the steps of: if the identity recognition fails and the fatigue is judged, storing the first electroencephalogram data; and training and generating a corresponding classifier according to the first electroencephalogram data and the second electroencephalogram data. In this embodiment, after storing the fatigue electroencephalogram data of the new user, i.e. the first electroencephalogram data, and the non-fatigue electroencephalogram data, i.e. the second electroencephalogram data, the new user trains and generates the personal classifier corresponding to the new user. The personal classifier is convenient for being used next time, the identity can be accurately identified, and the corresponding personal classifier is used for improving the accuracy of fatigue judgment. Preferably, the training of the classifier is performed using a convolutional neural network. Preferably, the blood oxygen data of the new user in normal and fatigue are simultaneously stored, and training of the classifier is completed together with the electroencephalogram data, so that the accuracy is further improved.
An embodiment of the present invention provides a computing device, including: a processor adapted to implement various instructions; a memory adapted to store a plurality of instructions, the instructions adapted to be loaded by the processor and to perform the fatigue monitoring method of any of the preceding embodiments.
An embodiment of the present invention provides a storage medium, where the storage medium stores a plurality of instructions, and the instructions are adapted to be loaded by a processor and to execute the fatigue monitoring method in any one of the foregoing embodiments.
The embodiments disclosed herein may be implemented in hardware, software, firmware, or a combination of these implementations. Embodiments of the application may be implemented as computer programs or program code executing on programmable systems comprising at least one processor, a storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. Program code may be applied to input instructions to perform the functions described herein and generate output information. The output information may be applied to one or more output devices in a known manner. For purposes of this application, a processing system includes any system having a processor such as, for example, a Digital Signal Processor (DSP), a microcontroller, an Application Specific Integrated Circuit (ASIC), or a microprocessor.
The program code may be implemented in a high level procedural or object oriented programming language to communicate with a processing system. The program code can also be implemented in assembly or machine language, if desired. Indeed, the mechanisms described in this application are not limited in scope to any particular programming language. In any case, the language may be a compiled or interpreted language.
In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried by or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed via a network or via other computer readable media. Thus, a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), including, but not limited to, floppy diskettes, optical disks, read-only memories (CD-ROMs), magneto-optical disks, read-only memories (ROMs), Random Access Memories (RAMs), erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, flash memory, or a tangible machine-readable memory for transmitting information (e.g., carrier waves, infrared digital signals, etc.) using the internet in an electrical, optical, acoustical or other form of propagated signal. Thus, a machine-readable medium includes any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).
In the drawings, some features of the structures or methods may be shown in a particular arrangement and/or order. However, it is to be understood that such specific arrangement and/or ordering may not be required. Rather, in some embodiments, the features may be arranged in a manner and/or order different from that shown in the illustrative figures. In addition, the inclusion of a structural or methodical feature in a particular figure is not meant to imply that such feature is required in all embodiments, and in some embodiments, may not be included or may be combined with other features.
It should be noted that, all the modules/units mentioned in the embodiments of the apparatuses in this application are logical modules/units, and physically, one logical module/unit may be one physical module/unit, or may be a part of one physical module/unit, and may also be implemented by a combination of multiple physical modules/units, where the physical implementation manner of the logical modules/units itself is not the most important, and the combination of the functions implemented by the logical modules/units is the key to solve the technical problem proposed in this application. Furthermore, in order to highlight the innovative part of the present application, the above-mentioned embodiments of the apparatus of the present application do not introduce modules/units that are not so closely related to solve the technical problems presented in the present application, which does not indicate that there are no other modules/units in the above-mentioned embodiments of the apparatus.
While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those skilled in the art that the foregoing is a more detailed description of the invention, taken in conjunction with the specific embodiments thereof, and that no limitation of the invention is intended thereby. Various changes in form and detail, including simple deductions or substitutions, may be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (25)
1. A fatigue monitoring device, comprising:
the shell is made of flexible materials, and a through hole is formed in the first surface of the shell along a first direction;
the FPC board is arranged inside the shell and provided with a micro control unit;
the electroencephalogram acquisition electrode penetrates through the through hole and is arranged on the first surface, the electroencephalogram acquisition electrode is electrically connected with the micro control unit, and the electroencephalogram acquisition electrode is used for acquiring electroencephalogram signals of the forehead;
the first ear clip and the first connecting part are connected with the first ear clip and the shell, the first ear clip comprises first magnetic suction parts which are symmetrically arranged, a bias collecting electrode and a reference collecting electrode are arranged on the first magnetic suction parts, and the bias collecting electrode and the reference collecting electrode are electrically connected with the micro control unit;
second ear clamp and second connecting portion, the second connecting portion are connected the second ear clamp with the casing, first connecting portion with second connecting portion symmetry set up in the both ends of second direction are followed to the casing, the second ear clamp is including the second magnetism portion of inhaling that the symmetry set up, be provided with blood oxygen collector on the second magnetism portion of inhaling, blood oxygen collector with little the control unit electricity is connected, little the control unit with the second magnetism portion electricity is inhaled and is connected.
2. The fatigue monitoring device of claim 1, wherein the first ear clip, and/or the second ear clip, comprises symmetrically disposed flexures that connect the first magnetically attractive portion and the first coupling portion, and/or connect the second magnetically attractive portion and the second coupling portion.
3. The fatigue monitoring device of claim 1, wherein the number of the electroencephalogram acquisition electrodes is plural, the number of the through holes is the same as that of the electroencephalogram acquisition electrodes, the plural electroencephalogram acquisition electrodes are arranged at intervals along the second direction, and the distance between the electroencephalogram acquisition electrodes positioned at both ends along the second direction is 60mm-100 mm.
4. The fatigue monitoring device according to claim 1, further comprising a strap, wherein strap holes are provided at both ends of the housing in the second direction, and the strap is connected to the housing through the strap holes.
5. The fatigue monitoring device of claim 1, further comprising a key portion recessed in the second face of the housing along the first direction, the key portion being electrically connected to the micro-control unit.
6. The fatigue monitoring device of claim 5, further comprising a status light disposed on the second side, the status light being electrically connected to the micro-control unit.
7. The fatigue monitoring device of claim 5, further comprising a power source and a magnetic USB interface, wherein the power source is disposed in the housing, the power source is electrically connected to the micro control unit and the magnetic USB interface, and the magnetic USB interface is concavely disposed on the second surface.
8. The fatigue monitoring device of claim 1, wherein a wireless transmission unit is further disposed on the FPC board, and the wireless transmission unit is electrically connected with the micro control unit.
9. The fatigue monitoring device of claim 1, further comprising a microphone disposed on the housing, the microphone being electrically connected to the micro-control unit, the microphone being configured to collect an audio signal.
10. The fatigue monitoring device of claim 1, further comprising a speaker disposed on the housing, the speaker being electrically connected to the micro-control unit, the speaker being configured to output a voice prompt.
11. The fatigue monitoring device of claim 1, wherein the micro control unit comprises an active electrode conversion unit, a multistage filtering and amplifying unit, an analog-to-digital conversion unit and a microprocessor which are electrically connected in sequence, and the active electrode conversion unit is electrically connected with the electroencephalogram acquisition electrode.
12. A method of fatigue monitoring, comprising the steps of:
acquiring first electroencephalogram data and first blood oxygen data;
processing the first electroencephalogram data and the first blood oxygen data respectively to obtain an electroencephalogram characteristic and a blood oxygen characteristic;
and inputting the electroencephalogram characteristics and the blood oxygen characteristics into a classifier for fatigue judgment.
13. The fatigue monitoring method of claim 12, wherein before the step of processing the first electroencephalogram data and the first blood oxygen data to obtain an electroencephalogram characteristic and a blood oxygen characteristic, respectively, the method further comprises the following steps:
acquiring pre-sampled second electroencephalogram data;
inputting the second electroencephalogram data into an identity recognition model for identity recognition;
and if the identity recognition fails, storing the second electroencephalogram data.
14. The fatigue monitoring method of claim 13, wherein the identity recognition model is trained using a convolutional neural network.
15. The fatigue monitoring method of claim 13, further comprising the steps of:
and training and updating the identity recognition model according to the second electroencephalogram data.
16. The fatigue monitoring method of claim 13, wherein said step of inputting said electroencephalogram characteristic and said blood oxygen characteristic into a classifier for fatigue determination comprises:
if the identity recognition is successful, inputting the electroencephalogram feature and the blood oxygen feature into a specific classifier corresponding to the recognized identity information for fatigue judgment;
and if the identity recognition fails, inputting the electroencephalogram characteristic and the blood oxygen characteristic into a general classifier for fatigue judgment.
17. The fatigue monitoring method of claim 12, wherein the electroencephalogram feature comprises a functional connectivity feature, a non-linear dynamics feature, a power spectrum feature, and the blood oxygen feature comprises a blood oxygen saturation variability feature.
18. The fatigue monitoring method of claim 17, wherein the functional connection characteristic is a mutual information value corresponding to a theta wave, an alpha wave, a beta wave, and a gamma wave in the first electroencephalogram data, the nonlinear dynamics characteristic is an approximate entropy corresponding to the theta wave, the alpha wave, the beta wave, and the gamma wave, and the power spectrum characteristic is a power ratio corresponding to the theta wave, the alpha wave, the beta wave, and the gamma wave.
19. The fatigue monitoring method of claim 18, further comprising the steps of:
obtaining pre-sampled second blood oxygen data, and calculating to obtain an average value P of the blood oxygen saturation in the second blood oxygen dataref；
Calculating the blood oxygen saturation variability characteristic of (P/P) according to the blood oxygen saturation value P of the first blood oxygen dataref)4。
20. The fatigue monitoring method according to claim 19, wherein said blood oxygen saturation variability feature obtained in said calculating is (P/P)ref)4Before the step (2), further comprising the steps of:
processing the first blood oxygen data and the second blood oxygen data to remove outliers less than 85.
21. The fatigue monitoring method of claim 12, further comprising the steps of:
if the fatigue is judged, the electric stimulation is output.
22. The fatigue monitoring method of claim 12, further comprising the steps of:
if the fatigue is judged, a voice prompt is played.
23. The fatigue monitoring method of claim 15, further comprising the steps of:
if the identity recognition fails and the fatigue is judged, storing the first electroencephalogram data;
and training and generating a corresponding classifier according to the first electroencephalogram data and the second electroencephalogram data.
24. A computing device, comprising:
a processor adapted to implement various instructions;
a memory adapted to store a plurality of instructions adapted to be loaded by the processor and to perform the fatigue monitoring method of any of claims 12-23.
25. A storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the fatigue monitoring method of any of claims 12-23.
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