A neurology safety monitoring method and system

Abstract

The present invention proposes a neurology safety monitoring method and system. The neurology safety monitoring system includes a smart mobile terminal, a smart glasses monitoring device and a smart bracelet. The smart mobile terminal is respectively connected to the smart glasses monitoring device and the smart bracelet for communication. The smart glasses monitoring device includes a display device, a microphone, a micro camera, a speaker, a processor and a first acceleration sensor. The smart bracelet includes a photoelectric sensor, a second acceleration sensor and a body temperature sensor. In the present invention, the neurology safety monitoring system uses smart wearable devices represented by smart glasses and smart bracelets to realize real-time status monitoring of users, thereby improving the portability of the detection equipment.

Description

Technical Field

[0001] The invention relates to the field of clinical nursing, and in particular to a neurology safety monitoring method and system. Background Art

[0002] The Department of Neurology is a secondary discipline related to nerves, and mainly treats cerebrovascular diseases (cerebral infarction, cerebral hemorrhage), migraine, brain inflammatory diseases (encephalitis, meningitis), myelitis, epilepsy, dementia, metabolic diseases and genetic diseases, trigeminal neuralgia, sciatica, peripheral neuropathy and myasthenia gravis, etc. The main examination methods include head and neck MRI, CT, ECT, PETCT, EEG, TCD (transcranial Doppler ultrasound), electromyography, evoked potential and blood rheology examination, genetic diagnosis, etc. At the same time, we cross-diagnose and treat functional diseases such as neurasthenia and insomnia with the Department of Psychology.

[0003] Neurological nursing mainly refers to comprehensive and continuous nursing activities for patients with nervous system-related diseases. The entire nursing process is relatively complex, including monitoring of the patient's physical condition, guidance and management of drug use, and assistance in rehabilitation training. It is committed to maintaining the patient's physiological and psychological state and restoring the normal function of the nervous system. Neurological nursing is highly professional. It is an important part of the treatment of neurological diseases and is related to the patient's recovery. Monitoring of physical condition is the basis of the entire nursing process. Currently, fixed sensors are mostly used to monitor physical condition. Although the data accuracy is high, the portability is poor and real-time condition monitoring cannot be achieved. Summary of the invention

[0004] In order to solve the technical problem that the body monitoring equipment in the prior art is poor in portability and cannot realize real-time condition monitoring, the neurology safety monitoring system proposed in the present invention includes a smart mobile terminal, a smart glasses monitoring device and a smart bracelet, and the smart mobile terminal is respectively communicated with the smart glasses monitoring device and the smart bracelet;

[0005] The smart glasses monitoring device includes a display device, a sound pickup, a micro camera, a speaker, a processor and a first acceleration sensor;

[0006] The smart bracelet includes a photoelectric sensor, a second acceleration sensor and a body temperature sensor.

[0007] Preferably, the display device includes a display device and a camera, the display device is provided with a cover plate, a connecting layer, a polarizing layer, a transparent OLED panel and an electrochromic layer from top to bottom, an installation groove is provided at a central position of the transparent OLED panel and the electrochromic layer, and the camera is provided in the installation groove.

[0008] Preferably, the working state of the display device is divided into a detection state and a non-detection state.

[0009] Preferably, in the non-detection state, the electrochromic layer is in a transparent state, the transparent OLED panel and the camera are in a non-working state, the external ambient light can pass through the display device to reach the user's eyes, and the user can observe normally.

[0010] Preferably, in the detection state, the electrochromic layer is in a reflective state, the transparent OLED panel displays a predetermined picture, the camera captures an image of pupil changes under the stimulation of the picture, and the pupil change image is transmitted to the smart mobile terminal through the processor, and the smart mobile terminal calculates the pupil contraction speed based on the pupil change image.

[0011] Preferably, the pupil contraction speed is calculated by counting the number of picture frames in which the eyes are opened as wide as possible and closed as small as possible, and obtaining the total time of contraction change based on the time of each frame as the pupil contraction speed.

[0012] Preferably, the functions implemented by the intelligent mobile terminal include status alarm and status monitoring.

[0013] Preferably, in the status alarm, the smart mobile terminal determines whether the user has symptoms of nerve convulsion based on the data of the first acceleration sensor, and the smart mobile terminal determines whether the user has an expression of extreme pain based on the image data collected by the micro camera. If the user has symptoms of nerve convulsion, or the user has an expression of extreme pain, the smart mobile terminal will automatically contact a doctor for help, and send out an alarm through the speaker to ask for help from people around.

[0014] Preferably, in the status monitoring, the smart mobile terminal receives body temperature data and heart rate data from the smart bracelet, determines the user's emotional state based on the voice signal and facial image from the smart glasses monitoring device, detects the pupil contraction speed based on the user's activity state, and inputs a variety of detection data into a neural network model to determine the user's health status.

[0015] The neurology safety monitoring method proposed in the present invention is based on the above-mentioned neurology safety monitoring system, and the neurology safety monitoring method specifically includes the following steps:

[0016] S1, judging whether an emergency situation occurs according to the acceleration data and image data of the smart glasses monitoring device, if an emergency situation occurs, proceed to S2, otherwise, proceed to S3;

[0017] S2. The smart mobile terminal will automatically contact a doctor for help, sound an alarm, ask for help from people around, and end safety monitoring;

[0018] S3. Acquire detection data of the smart bracelet and the smart glasses monitoring device, input the detection data into a neural network model, and determine the user's health status.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] The neurology safety monitoring system uses smart wearable devices such as smart glasses and smart bracelets to achieve real-time condition monitoring of users, improving the portability of detection equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a structural schematic diagram of the neurology safety monitoring system of the present invention;

[0022] Figure 2 It is a schematic diagram of the structure of the smart glasses monitoring device of the present invention;

[0023] Figure 3 It is a schematic structural diagram of the display device of the present invention. DETAILED DESCRIPTION

[0024] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0025] like Figure 1 As shown, the neurology safety monitoring system proposed in the present invention includes a smart mobile terminal, a smart glasses monitoring device and a smart bracelet, and the smart mobile terminal is respectively communicated with the smart glasses monitoring device and the smart bracelet.

[0026] like Figure 2 As shown, the smart glasses monitoring device includes a display device 1, a sound pickup 2, a micro camera 3, a speaker 4, a processor 5 and a first acceleration sensor 6. The display device 1 is arranged in the frame, the sound pickup 2 is arranged on the upper surface of the middle beam, the micro camera 3 is arranged at the position where the temple is connected to the pile head, the speaker 4 is arranged in the middle position of the temple, the processor 5 is arranged between the micro camera and the speaker of the right temple, and the first acceleration sensor 6 is arranged at the tail position of the temple.

[0027] The display device 1 is used for pupil detection, such as Figure 3As shown, the display device 1 includes a display device 11 and a camera 12. The display device 11 is provided with a cover plate 111, a connection layer 112, a polarizing layer 113, a transparent OLED panel 114 and an electrochromic layer 115 from top to bottom. The cover plate 111 is used to protect the transparent OLED panel 114 to prevent water vapor, dust and the like in the air from affecting the transparent OLED panel 114. A cover glass can be selected. The connection layer 112 can be made of optical glue, and the polarizing layer 113 can be made of a polarizer. The transparent OLED panel 114 includes an anode layer, a light-emitting layer and a metal cathode layer from top to bottom. The anode layer and the metal cathode layer are used for conduction. The anode layer adopts an ITO film, and the metal cathode layer adopts a transparent metal film. When the transparent OLED panel 114 does not emit light, the transmittance reaches more than 85%. The electrochromic layer 115 is composed of an upper substrate material layer, an upper transparent conductive layer, an electrochromic material layer, an electrolyte layer, an ion storage layer, a lower transparent conductive layer and a lower substrate material layer in sequence. When a voltage is applied to both ends of the ion storage layer and the electrochromic material layer, some ions present in the ion storage layer are transmitted to the electrochromic material layer through the electrolyte layer. Once the electrochromic material layer has ions injected, it can be transformed into a transparent state. Reversing the voltage applied between the electrochromic material layer and the ion storage layer can cause the ions to be transferred back to the ion storage layer, thereby re-transforming into a reflective state. The switching time between the transparent state and the reflective state is 50 to 2000 ms, and the switching voltage is 0.25-3V. An installation groove 116 is set at the central position of the transparent OLED panel 114 and the electrochromic layer 115, and the camera 12 is placed in the installation groove 116. The camera 12 uses a front camera module for mobile phones produced by Sunny Optical Co., Ltd.

[0028] The working state of the display device 1 is divided into a detection state and a non-detection state. In the non-detection state, the electrochromic layer 115 is in a transparent state, the transparent OLED panel 114 and the camera 12 are in a non-working state, and the external ambient light can reach the user's eyes through the display device 1, so that the user can observe normally. In the detection state, the electrochromic layer 115 is in a reflective state, the transparent OLED panel 114 displays a predetermined picture, and the camera 12 captures the pupil change image under the stimulation of the picture, and transmits the pupil change image to the smart mobile terminal through the processor 5. The smart mobile terminal calculates the pupil contraction speed according to the pupil change image. The calculation method of the pupil contraction speed is to count the number of picture frames from the eyes being wide open to the closed to the smallest, and obtain the total time of contraction change according to the time of each frame as the pupil contraction speed. Many studies have found that as the intracranial pressure increases, one side of the pupil dilates first, and then bilateral pupil dilation occurs. The pupil reaction rate is negatively correlated with the intracranial pressure. Therefore, the smart mobile terminal can roughly judge the level of intracranial pressure according to the pupil contraction speed.

[0029] The microphone 2 is used to collect the voice signal of the user's conversation with others, and transmit it to the intelligent mobile terminal through the processor 5. The intelligent mobile terminal determines the user's emotional state according to the voice signal. The microphone 2 can be selected from the CS-05A miniature high-fidelity microphone of Shenzhen Yianda Electronics Co., Ltd.

[0030] The micro camera 3 is used to collect the user's facial image and transmit it to the smart mobile terminal through the processor 5. The smart mobile terminal determines the user's emotional state based on the facial image. The micro camera 3 can adopt the G1-OV 12D40 three-axis anti-shake gimbal module of Shenzhen Huaxing Video Technology Co., Ltd.

[0031] The loudspeaker 4 is used to play a prompt tone or issue an alarm.

[0032] The smart bracelet includes a photoelectric sensor, a second acceleration sensor and a body temperature sensor. The photoelectric sensor uses photoelectric volumetric pulse wave recording to detect the user's heart rate. The detection data of the smart bracelet is transmitted to the smart mobile terminal.

[0033] The intelligent mobile terminal adopts a smart phone, and the functions implemented by it include: 1) status alarm, the intelligent mobile terminal determines whether the user has symptoms of nerve twitching according to the data of the first acceleration sensor 6, and determines whether the user has an extremely painful expression according to the image data collected by the micro camera 3. If the user has symptoms of nerve twitching, or the user has an extremely painful expression, it means that an emergency has occurred, and the intelligent mobile terminal will automatically contact a doctor for help, and send an alarm through the speaker 4 to ask for help from people around; 2) status monitoring, the intelligent mobile terminal receives body temperature data and heart rate data from the smart bracelet, determines the user's emotional state according to the voice signal and facial image from the smart glasses monitoring device, and detects the pupil contraction speed according to the user's activity state, and inputs a variety of detection data into a pre-trained neural network model to determine the user's health state. The specific process of detecting the pupil contraction speed according to the user's activity state is that if the user is in a non-communication static state, the speaker 4 prompts the user to perform pupil contraction speed detection, and detects the user's feedback information through the first acceleration sensor 6. If the user does not shake his head, the display device 1 is adjusted to the detection state, and the pupil change image is obtained. The intelligent mobile terminal calculates the pupil contraction speed based on the pupil change image. The process of determining the non-communicative static state is to determine whether the user is in a static state based on the data of the first acceleration sensor and the second acceleration sensor. When in a static state, the voice signal from the microphone is analyzed to determine whether the user's voice exists. If the user's voice does not exist, it means that the user is in a non-communicative static state. The neural network model is implemented based on the MobileNet lightweight network model launched by Google, which has a smaller size, less calculation and higher accuracy.

[0034] Based on the above neurology safety monitoring system, the neurology safety monitoring method specifically includes the following steps:

[0035] S1. Determine whether an emergency situation occurs based on the acceleration data and image data of the smart glasses monitoring device. If an emergency situation occurs, enter S2; otherwise, enter S3.

[0036] S2. The smart mobile terminal will automatically contact a doctor for help, sound an alarm, and ask for help from people around to end safety monitoring.

[0037] S3. Obtain the detection data of the smart bracelet and smart glasses monitoring devices, input the detection data into the neural network model, and judge the user's health status.

[0038] The above disclosure is only the preferred embodiment of the present invention, and certainly cannot be used to limit the scope of the present invention. It should be pointed out that for those skilled in the art, any equivalent changes made to the scheme of the present invention without departing from the design structure and principle of the present invention are considered to be within the protection scope of the present invention.

Claims

1. A neurology safety monitoring system, characterized in that ,The neurology safety monitoring system includes a smart mobile terminal, a smart glasses monitoring device and a smart wristband, and the smart mobile terminal is respectively communicatively connected with the smart glasses monitoring device and the smart wristband; The smart glasses monitoring device includes a display device, a sound pickup, a micro camera, a speaker, a processor and a first acceleration sensor; The smart bracelet includes a photoelectric sensor, a second acceleration sensor and a body temperature sensor; The display device comprises a display device and a camera, wherein the display device is provided with a cover plate, a connection layer, a polarizing layer, a transparent OLED panel and an electrochromic layer from top to bottom, a mounting groove is provided at the central position of the transparent OLED panel and the electrochromic layer, and the camera is provided in the mounting groove; The working state of the display device is divided into a detection state and a non-detection state. Whether the user is in a non-communicative static state is determined according to the data of the first acceleration sensor, the second acceleration sensor and the microphone. If the user is in a non-communicative static state, the speaker prompts the user to perform pupil contraction speed detection. The first acceleration sensor is used to detect whether the user shakes his head. If the user does not shake his head, the display device is adjusted to a detection state. If the user is not in a non-communicative static state, or the user is in a non-communicative static state but the user refuses to perform pupil contraction speed detection by shaking his head, the display device is adjusted to a non-detection state. In the non-detection state, the electrochromic layer is in a transparent state, the transparent OLED panel and the camera are in a non-working state, and the external ambient light can pass through the display device to reach the user's eyes, so the user can observe normally; In the detection state, the electrochromic layer is in a reflective state, the transparent OLED panel displays a predetermined picture, the camera captures an image of pupil changes under the stimulation of the picture, and transmits the pupil change image to the smart mobile terminal through the processor. The smart mobile terminal calculates the pupil contraction speed according to the pupil change image, and determines the level of intracranial pressure according to the pupil contraction speed.

2. The neurology safety monitoring system according to claim 1, characterized in that: The pupil contraction speed is calculated by counting the number of picture frames in which the eyes are wide open and narrow closed, and obtaining the total time of contraction change according to the time of each frame as the pupil contraction speed.

3. The neurology safety monitoring system according to claim 1, characterized in that: The functions implemented by the intelligent mobile terminal include status alarm and status monitoring.

4. The neurology safety monitoring system according to claim 3, characterized in that: In the status alarm, the smart mobile terminal determines whether the user has symptoms of nerve convulsion based on the data of the first acceleration sensor, and determines whether the user has an extremely painful expression based on the image data collected by the micro camera. If the user has symptoms of nerve convulsion, or the user has an extremely painful expression, the smart mobile terminal will automatically contact a doctor for help, and issue an alarm through the speaker to ask for help from people around.

5. The neurology safety monitoring system according to claim 4, characterized in that: In the status monitoring, the smart mobile terminal receives the body temperature data and heart rate data from the smart bracelet, determines the user's emotional state based on the voice signal and facial image from the smart glasses monitoring device, detects the pupil contraction speed based on the user's activity status, and inputs a variety of detection data into the neural network model to determine the user's health status.

6. A neurology safety monitoring method, based on the neurology safety monitoring system according to any one of claims 1 to 5, characterized in that: The neurology safety monitoring method specifically comprises the following steps: S1, judging whether an emergency situation occurs according to the acceleration data and image data of the smart glasses monitoring device, if an emergency situation occurs, proceed to S2, otherwise, proceed to S3; S2. The smart mobile terminal will automatically contact a doctor for help, sound an alarm, ask for help from people around, and end safety monitoring; S3. Acquire detection data of the smart bracelet and the smart glasses monitoring device, input the detection data into a neural network model, and determine the user's health status.

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