CN113425271B - Daytime operation discharge judgment method, device, equipment and storage medium - Google Patents
Daytime operation discharge judgment method, device, equipment and storage medium Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 64
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Abstract
The application provides a daytime operation discharge judgment method, device, equipment and storage medium, wherein the method comprises the following steps: determining the blood pressure and pulse fluctuation condition of the patient according to the preoperative and current blood pressure data and pulse data of the patient; determining the current gait condition of the patient according to the current walking video data of the patient; determining a current pain level of the patient based on the current facial image data of the patient; and (5) judging whether the patient can be discharged or not by combining the blood pressure and pulse fluctuation condition, gait condition and pain degree of the patient. By the application of the method and the device, whether a patient undergoing daytime operation can be discharged or not can be accurately assessed based on the computer equipment, so that the burden of medical staff is greatly reduced.
Description
Technical Field
The application belongs to the technical field of internet medical treatment, and particularly relates to a daily operation discharge judgment method, device, equipment and storage medium.
Background
The daytime operation means that the patient admission, completion and discharge of the patient are completed within 1 to 2 working days, except for the outpatient operation and the emergency operation performed in a doctor's office or hospital. The principle of the daytime operation is that the interference on the physiological functions of the mechanism is small, the operation risk is small, the operation time is short, the expected bleeding amount is small, the postoperative complications are small, the postoperative pain degree is light, and the incidence rate of nausea and vomiting is low, so that the daytime operation has the advantages of obviously shortening the hospitalization time, accelerating the turnover of a surgical bed, reducing the nosocomial infection, improving the use efficiency of medical resources and the like, and the medical care and confirmation of patients, medical staff and health administration departments are obtained.
At present, whether a patient can discharge in daytime operation mainly is judged through the subjective of medical staff, so that the patient has strong subjective factors, and the workload of the medical staff is heavier due to the fact that the daily operation amount is more and more.
Therefore, there is a need for a method, apparatus, device and storage medium for determining discharge of a day operation, which are applied to a computer device, so as to assist medical staff in performing discharge evaluation of the day operation, thereby reducing the burden of the medical staff.
Disclosure of Invention
The application provides a method, a device, equipment and a storage medium for judging discharge of daytime operation, which can accurately evaluate whether a patient carrying out the daytime operation can discharge based on computer equipment so as to greatly reduce the burden of medical staff.
An embodiment of a first aspect of the present application provides a method for determining discharge of a day operation, the method including:
determining the blood pressure and pulse fluctuation conditions of a patient according to preoperative and current blood pressure data and pulse data of the patient;
determining the current gait condition of the patient according to the current walking video data of the patient;
determining a current pain level of the patient from current facial image data of the patient;
and judging whether the patient can be discharged or not according to the blood pressure and pulse fluctuation condition, the gait condition and the pain degree of the patient.
Optionally, the determining whether the patient can be discharged from the hospital by integrating the blood pressure and pulse fluctuation condition, the gait condition and the pain degree of the patient includes:
determining a fluctuation judgment factor according to the blood pressure and pulse fluctuation conditions and a preset fluctuation judgment corresponding relation;
determining a gait judgment factor according to the gait condition and a preset gait judgment corresponding relation;
determining a pain judging factor according to the pain degree and a preset pain judging corresponding relation;
determining the sum of the fluctuation judgment factor, the gait judgment factor and the pain judgment factor as an anesthesia degree value of the patient;
and judging that the patient can be discharged according to the anesthesia degree value being larger than a preset threshold value, or else, the patient cannot be discharged.
Optionally, before determining the blood pressure and pulse fluctuation condition of the patient according to the pre-operation and current blood pressure data and pulse data of the patient, the method further comprises:
acquiring preoperative and current blood pressure data and pulse data of the patient through a patient management system;
and acquiring current walking video data of the patient and current facial image data of the patient through an image acquisition device.
Optionally, the determining the blood pressure and pulse fluctuation condition of the patient according to the pre-operation and current blood pressure data and pulse data of the patient includes:
determining the blood pressure and pulse fluctuation coefficient of a patient according to the pre-operation and current blood pressure data and pulse data of the patient by the following formula:
wherein f represents the blood pressure and pulse fluctuation coefficient, P a Indicating the current blood pressure of the patient, P b Representing the pre-operative blood pressure of the patient, M a Representing the current pulse of the patient M b Representing the pre-operative pulse of the patient.
Optionally, the determining the current gait condition of the patient according to the current walking video data of the patient includes:
determining the completion degree of standing walking and the completion degree of starting a squatting post station in the current walking process of the patient according to the current walking video data of the patient;
and determining the current gait condition of the patient according to the standing walking completion degree and the squatting post-station starting completion degree of the patient respectively.
Optionally, the determining the standing walking completion degree of the patient in the current walking process according to the current walking video data of the patient includes:
if the current walking video data of the patient is empty, determining that the patient cannot walk at all; if the pixel values of the current walking video data of the patient are all larger than or equal to the preset pixel values, determining that the patient can walk only by being assisted by other people;
if the current walking video data of the patient is not empty and the pixel value of the current walking video data of the patient is smaller than the preset pixel value, respectively calculating the upper datum line change angle theta of the patient in the appointed time according to the following formula according to the current walking video data of the patient u And the lower datum line changes angle theta d ：
Wherein the saidAn upper datum line slope of a patient in the video data of the initial frame in the appointed time; said->The slope of the upper datum line of the patient in the last frame of video data in the appointed time is given; said->A lower baseline slope for the patient in the video data for the initial frame within the specified time,/a>A slope of a lower datum line of a patient in the last frame of video data in the appointed time; the upper reference line is a connecting line between the center of the neck of the patient and the centers of the left and right buttocks of the patient; the lower reference line is a line connecting the centers of the left and right buttocks of the patient and the centers of the left and right ankles of the patient;
changing the angle theta according to the upper datum line u And the lower datum line change angle theta d And determining the completion degree of standing and walking of the patient according to a preset completion degree judging rule.
Optionally, the determining the completion degree of the start of the squat post-station of the patient according to the current walking video data of the patient comprises:
if the current walking video data of the patient is empty, determining that the patient cannot stand up after squatting;
if the current walking video data of the patient is not empty, determining the starting completion degree of the squatting post-station of the patient according to the following formula based on the current walking video data of the patient:
d f ＝|d last -d first |
wherein said d first A vertical distance between the center of the left and right buttocks of the patient and the center of the left and right ankle of the patient in the initial frame video data in the appointed time; said d last The vertical distance between the center of the left hip and the right hip of the patient and the center of the left ankle and the right ankle of the patient in the last frame of video data in the appointed time is set; the fps is the shooting speed of the video data in the specified time; f is the total frame number of the video data in the appointed time; said d f A difference value of a vertical distance between the centers of the left and right buttocks of the patient and the centers of the left and right ankle of the patient in the specified time; the v is the movement speed of the buttocks of the patient in the vertical direction within the specified time;
and determining the starting completion degree of the squatting post-station of the patient according to the movement speed of the buttocks of the patient in the vertical direction within the appointed time.
Optionally, the determining the current pain degree of the patient according to the current facial image data of the patient includes:
and determining the current pain degree of the patient according to the current facial image data of the patient and the trained facial recognition model.
Embodiments of a second aspect of the present application provide a day-time surgical discharge judgment device, the device including:
the first determining module is used for determining the blood pressure and pulse fluctuation condition of the patient according to the pre-operation and current blood pressure data and pulse data of the patient;
the second determining module is used for determining the current gait condition of the patient according to the current walking video data of the patient;
a third determining module for determining a current pain level of the patient from the current facial image data of the patient;
and the comprehensive judging module is used for integrating the blood pressure and pulse fluctuation condition, the gait condition and the pain degree of the patient and judging whether the patient can be discharged.
Embodiments of the third aspect of the present application provide a computer-assisted device comprising a processor, a memory and a computer program stored on the memory and capable of running on the processor, the processor running the computer program to implement a method as described in the first aspect.
Embodiments of the fourth aspect of the present application provide a computer readable storage medium having stored thereon a computer program for execution by a processor to perform the method of the first aspect.
The technical scheme provided in the embodiment of the application has at least the following technical effects or advantages:
according to the daytime operation discharge judgment method provided by the embodiment of the application, whether the anesthesia efficacy of a daytime operation patient completely subsides is determined by combining three index data of the blood pressure and pulse fluctuation condition, gait condition and pain degree, and physiological characteristics and external appearance characteristics of the patient can be simultaneously considered, so that the accuracy of a judgment result (especially judgment of the disappearance of the anesthesia efficacy of the patient) is ensured to the greatest extent, and erroneous judgment is avoided or reduced as much as possible; the method is convenient to realize without complex physiological characteristics or an electroencephalogram signal acquisition system, and is more suitable for the daytime operation environment, so that medical staff is assisted in accurately judging whether a patient undergoing the daytime operation can be discharged or not, and the burden of the medical staff is greatly reduced.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures.
In the drawings:
fig. 1 is a schematic flow chart of a daily operation discharge judgment method according to an embodiment of the present application;
fig. 2 shows a schematic structural diagram of a daily operation discharge judgment device according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs.
A day-time operation discharge judgment method, apparatus, device, and storage medium according to embodiments of the present application are described below with reference to the accompanying drawings.
The embodiment designs a method for accurately judging whether a day operation can be discharged through computer equipment, researches on factors influencing discharge of patients in the day operation at present are conducted, and researches find that: the day operation is usually a minor operation, and the success rate is extremely high, and mainly the anesthetic efficacy is not completely resolved to affect the discharge of patients, so the key of determining whether the patient can discharge in the day operation is how to accurately judge whether the anesthetic efficacy of the patient is completely resolved, and the day operation discharge judgment method implemented based on computer equipment in the embodiment needs to solve how to accurately judge whether the anesthetic efficacy of the patient in the day operation is completely resolved through the computer equipment.
In view of the above-mentioned research, the embodiment of the application provides a method for judging discharge of daytime operation, which is applied to a computer device, and the method is used for determining whether the anesthetic efficacy of a patient subjected to the daytime operation is completely resolved by combining three index data, so that whether the patient subjected to the daytime operation can be discharged or not can be accurately judged, thereby assisting medical staff in accurately judging whether the patient subjected to the daytime operation can be discharged or not, and greatly reducing the burden of the medical staff. The computer device may be provided independently, or may be an existing medical management device or the like, so long as the following daytime operation discharge judgment method can be executed on the device. As shown in fig. 1, the method may include the steps of:
step S1, determining the blood pressure and pulse fluctuation condition of a patient according to the pre-operation and current blood pressure data and pulse data of the patient.
The pre-operation blood pressure data and pulse data of the patient can be generally understood as blood pressure data and pulse data of the patient before operation when the physical condition of the patient is normal, the data can be data collected from the patient, and standard data can be selected according to the age, sex, physical condition and the like of the patient, which is not particularly limited in this embodiment. The current blood pressure data and pulse data of the patient can be understood as blood pressure data and pulse data when the patient can be discharged or not, and are usually acquired from the patient.
In a specific implementation of this embodiment, the step S1 may include the following processes: according to the preoperative and current blood pressure data and pulse data of a patient, determining the blood pressure and pulse fluctuation coefficient of the patient according to the following formula (1):
wherein f represents the blood pressure and pulse fluctuation coefficient, P a Indicating the current blood pressure of the patient, P b Representing the pre-operative blood pressure of the patient, M a Representing the current pulse of the patient M b Representing the pre-operative pulse of the patient.
According to the above formula (1), the larger f indicates the larger the blood pressure difference and pulse difference before and after the operation, which indicates the larger the difference between the current physical state and the normal state of the patient, the smaller the possibility that the anesthetic efficacy is completely faded, and the more unfavorable the discharge.
And step S2, determining the current gait condition of the patient according to the current walking video data of the patient.
The current walking video data of the patient can be directly acquired by the image acquisition device or can be acquired from other medical auxiliary equipment, and the embodiment is not particularly limited to this. Gait conditions are understood to be the state of a patient when standing, walking, squatting, standing, etc. Because the anesthetic effect of the patient is often bad when the anesthetic effect acts, the anesthetic effect of the patient is often different from that of normal people when the patient stands, walks, squats, stands up and the like, and the larger the difference is, the smaller the anesthetic effect of the patient is, and the more unfavorable the patient is for discharge.
In another implementation manner of this embodiment, the step S2 may include the following processes: determining the completion degree of standing walking and the completion degree of starting a squatting post station in the current walking process of the patient according to the current walking video data of the patient; and determining the current gait condition of the patient according to the standing walking completion degree and the squatting post-station starting completion degree of the patient. Thus, the current gait condition of the patient is determined through the data (the completion of standing walking and the completion of starting of the squatting post-station), a more accurate judgment result can be obtained, and the accuracy of the daily operation discharge judgment method can be further ensured.
It should be noted that, the above-mentioned determination of the current gait condition of the patient by the standing walking completion degree and the squatting post-station starting completion degree is only a preferred implementation of the present embodiment, and the present embodiment is not limited thereto, and may also be determined by standing time and shaking frequency characteristics, for example.
Specifically, the determining the standing walking completion degree of the patient in the current walking process according to the current walking video data of the patient may include the following processes: if the current walking video data of the patient is empty, determining that the patient cannot walk at all; if the pixel values of the current walking video data of the patient are all larger than or equal to the preset pixel values, determining that the patient can walk only by being assisted by other people; if the current walking video data of the patient is not empty and the pixel value of the current walking video data of the patient is smaller than the preset pixel value, respectively calculating the upper datum line change angle theta of the patient in the appointed time according to the following formula according to the current walking video data of the patient u And the lower datum line changes angle theta d ：
Wherein,an upper baseline slope for the patient in the video data for the initial frame for the specified time; />The slope of the upper datum line of the patient in the last frame of video data in the appointed time; />Lower baseline slope for patient in video data for initial frame within specified time,/for patient in video data for initial frame within specified time>A lower datum line slope of a patient in the last frame of video data in a designated time; the upper datum line is a connecting line between the center of the neck of the patient and the centers of the left hip and the right hip of the patient; the lower reference line is a line connecting the centers of the left and right buttocks and the centers of the left and right ankles of the patient.
Can change the angle theta according to the upper datum line u And the lower datum line changes angle theta d And determining the completion degree of standing and walking of the patient according to a preset completion degree judging rule.
It will be appreciated that in a normal situation, when a normal person (a person who is healthy and is not anesthetized) is walking on his/her stand, the upper reference line and the lower reference line are the same straight line, and when the anesthetic effect is stronger, the upper reference line changes by an angle θ u And the lower datum line changes angle theta d The larger the rule, the more the preset completion degree judgment rule can be set according to the rule, and the specific setting can be performed according to the actual situation, which is not particularly limited in the embodiment.
In this embodiment, the walking video of the patient may be acquired in real time through the camera and transmitted to the computer device or the cloud end for joint point identification, and then the slope of the upper reference line of the patient in the video data of the initial frame within the specified time may be obtained according to the identified joint point positionPatient's upper baseline slope +.>Patient's lower baseline slope +.>Patient's lower baseline slope +.>Then calculating the upper datum line change angle theta according to the datum line slopes u And the lower datum line changes angle theta d . The specified time may be set according to actual needs, and may be, for example, several tens of seconds, several minutes, or the like, which is not particularly limited in this embodiment. In addition, it is also possible to collect video data in a plurality of specified times for judgment and then calculate a plurality of upper reference line change angles theta u And the lower datum line changes angle theta d And determining the final upper datum line change angle theta by adopting an averaging method u And the lower datum line changes angle theta d Further ensuring the accuracy of the judgment result.
Specifically, the above-mentioned joint points (including but not limited to the neck, left and right buttocks, left and right ankle) may be identified using a neural network model, which may be but not limited to a higherranet model, which may identify 17 joint points throughout the body by training a coco dataset (a large image dataset designed specifically for object detection, segmentation, human keypoint detection, semantic segmentation, and subtitle generation). In the present embodiment, only the variation angle θ of the upper reference line is calculated u And the lower datum line changes angle theta d Therefore, only five joint points of the neck, the left hip, the right ankle and the left ankle are needed to be identified, so that the calculated amount can be reduced, and the speed and the accuracy of the model can be improved. The method specifically comprises the steps of adjusting the number of the joint points marked in the coco data set, retraining the modified data set by using a HighHRNet model, and obtaining the joint points by using a final model.
It should be noted that, the use of the HigherHRNet model and the selection of the five joint points are only preferred embodiments of the present embodimentThe upper reference line change angle θ can be performed as long as at least the five joint points can be identified by training u And the lower datum line changes angle theta d And (3) judging. In addition, the present embodiment is not limited to training the HigherHRNet model using the coco data set, and training may be performed using pre-operative and post-operative video images of the patient, as long as the at least five joint points can be identified.
Further, the determining the completion degree of the start of the squat post-stop of the patient according to the current walking video data of the patient may include the following steps: if the current walking video data of the patient is empty, determining that the patient cannot stand up after squatting; if the current walking video data of the patient is not empty, determining the starting completion degree of the squatting post-station of the patient according to the following formula based on the current walking video data of the patient according to the calculation result:
d f ＝|d last -d first |
wherein d first For the vertical distance between the centers of the left and right buttocks and the centers of the left and right ankle of the patient in the initial frame video data in the appointed time; d, d last The vertical distance between the centers of the left and right buttocks and the centers of the left and right ankle of the patient in the last frame of video data in the appointed time is set; fps is the shooting speed of video data within a specified time; f is the total frame number of the video data in the appointed time; d, d f The difference value of the vertical distance between the centers of the left and right buttocks and the centers of the left and right ankle of the patient in the appointed time is obtained; v is the movement speed of the buttocks of the patient in the vertical direction within a specified time;
and determining the starting completion degree of the standing after the patient squats according to the movement speed of the buttocks of the patient in the vertical direction within the appointed time.
It will be appreciated that in general, a normal person (a person who is healthy and is not anesthetized) will tend to start a squatting-post-station relatively quickly, and the more powerful the anesthetic effect is, the worse the completion of the squatting-post-station (the slower the lifting speed, the tilting of the body during the lifting or the inability to lift, etc.), and therefore, based on this rule and the movement speed of the patient's buttocks in the vertical direction for a specified time, the completion of the patient's squatting-post-station start can be determined. It should be noted that, the degree of completion of the start-up of the patient's squatting after the patient's buttocks is determined according to the movement speed of the patient's buttocks in the vertical direction, but the preferred embodiment of the present invention is not limited thereto, and for example, the degree of completion of the start-up of the patient's squatting after the patient's buttocks is determined according to the movement speed of other articulation points (such as neck, lumbar, chest, shoulder, etc.) in the vertical direction.
And step S3, determining the current pain degree of the patient according to the current facial image data of the patient.
It will be appreciated that, in general, when the pain level of a patient is different, it has different facial images, and the facial images of different pain levels typically have specific characteristics (e.g., pixels, color distribution, etc.), so that the current pain level of the patient can be determined from the facial image data.
Specifically, the above step S3 may include the following processes: and determining the current pain degree of the patient according to the current facial image data of the patient and the trained facial recognition model. The face recognition model may be any model that can recognize the facial expression of the patient after training, which is not particularly limited in this embodiment. The training sample of the facial recognition model can adopt an image set in a large database, and can also collect facial images of patients under different pain degrees.
The steps S1, S2 and S3 may be executed in any order in series or in parallel, and the present embodiment is not limited thereto.
In another specific implementation of this embodiment, the above parameters may be saved by the patient management system, and accordingly, before the step S1, the step S2, and the step S3 are performed, a data acquisition step may further be included, where the data acquisition step may include the following processes: acquiring preoperative and current blood pressure data and pulse data of a patient through a patient management system; and acquiring current walking video data of the patient and current facial image data of the patient through an image acquisition device.
In this embodiment, the computer device may be connected to the patient management system and the image acquisition device (or may be connected to other auxiliary medical devices) so as to obtain pre-operation and current blood pressure data and pulse data of the patient, current walking video data and facial image data of the patient, and the like, and may also transmit the determination result to the display device, so that the medical staff may more intuitively determine whether the patient can be discharged.
And S4, judging whether the patient can be discharged or not by integrating the blood pressure and pulse fluctuation condition, gait condition and pain degree of the patient.
In this embodiment, the three index data of the blood pressure and pulse fluctuation condition, gait condition and pain degree are combined to determine whether the anesthesia efficacy of the patient in the daytime operation completely subsides, and the physiological characteristic and the external appearance characteristic of the patient can be considered simultaneously, so that erroneous judgment is avoided or reduced as much as possible, and then whether the patient in the daytime operation can be discharged can be accurately judged, thereby assisting the medical staff in accurately judging whether the patient in the daytime operation can be discharged, and greatly reducing the burden of the medical staff.
In another implementation manner of this embodiment, the step S4 may include the following processes: determining a fluctuation judgment factor according to the blood pressure and pulse fluctuation conditions and a preset fluctuation judgment corresponding relation; determining a gait judgment factor according to the gait condition and a preset gait judgment corresponding relation; determining a pain judging factor according to the pain degree and a preset pain judging corresponding relation; determining the sum of the fluctuation judgment factor, the gait judgment factor and the pain judgment factor as an anesthesia degree value of the patient; and judging that the patient can be discharged according to the anesthesia degree value being larger than the preset threshold value, or else, the patient cannot be discharged.
In this embodiment, three index data including blood pressure, pulse fluctuation, gait condition and pain degree can be quantized through preset corresponding relations, so that the anesthesia degree is quantized, whether the patient can be discharged from the hospital or not can be judged in a quantization mode through computer equipment, and accuracy of a judging result is further guaranteed. The preset threshold may be determined according to a total value of each of the judging factors, for example, ninety percent of the total value of each of the judging factors, which is not limited in this embodiment.
According to the daytime operation discharge judgment method provided by the embodiment, whether the anesthesia efficacy of a daytime operation patient completely subsides is determined by combining three index data of the blood pressure and pulse fluctuation condition, gait condition and pain degree, and physiological characteristics and external appearance characteristics of the patient can be simultaneously considered, so that the accuracy of a judgment result (especially the judgment of the disappearance of the anesthesia efficacy of the patient) is ensured to the greatest extent, and erroneous judgment is avoided or reduced as much as possible; the method is convenient to realize without complex physiological characteristics or an electroencephalogram signal acquisition system, and is more suitable for the daytime operation environment, so that medical staff is assisted in accurately judging whether a patient undergoing the daytime operation can be discharged or not, and the burden of the medical staff is greatly reduced.
Based on the same concept of the daytime operation discharge judgment method, the embodiment further provides a daytime operation discharge judgment device, as shown in fig. 2, including:
the first determining module is used for determining the blood pressure and pulse fluctuation condition of the patient according to the pre-operation and current blood pressure data and pulse data of the patient;
the second determining module is used for determining the current gait condition of the patient according to the current walking video data of the patient;
a third determining module for determining a current pain level of the patient based on the current facial image data of the patient;
the comprehensive judging module is used for integrating the blood pressure and pulse fluctuation condition, gait condition and pain degree of the patient and judging whether the patient can be discharged.
The daily operation discharge judgment device provided in this embodiment at least can realize the beneficial effects that can be realized by the daily operation discharge judgment method based on the same conception of the daily operation discharge judgment method, and is not described in detail herein.
Based on the same concept as the daytime operation discharge judgment method, the embodiment also provides a computer auxiliary device, which comprises a processor, a memory and a computer program stored on the memory and capable of running on the processor, wherein the processor runs the computer program to realize the method of any embodiment.
The daily operation discharge judgment device provided in this embodiment at least can realize the beneficial effects that can be realized by the daily operation discharge judgment method based on the same conception of the daily operation discharge judgment method, and is not described in detail herein.
Based on the same concept as the daytime operation discharge judgment method, the present embodiment also provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the method of any one of the above embodiments.
The daily operation discharge judgment device provided in this embodiment at least can realize the beneficial effects that can be realized by the daily operation discharge judgment method based on the same conception of the daily operation discharge judgment method, and is not described in detail herein.
It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
The foregoing is merely a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A day discharge judgment method, characterized in that the method comprises:
determining the blood pressure and pulse fluctuation conditions of a patient according to preoperative and current blood pressure data and pulse data of the patient;
determining the current gait condition of the patient according to the current walking video data of the patient; comprising the following steps: determining the completion degree of standing walking and the completion degree of starting a squatting post station in the current walking process of the patient according to the current walking video data of the patient; determining the current gait condition of the patient according to the standing walking completion degree and the squatting post-station starting completion degree of the patient respectively;
determining a current pain level of the patient from current facial image data of the patient;
judging whether the patient can be discharged from the hospital or not by integrating the blood pressure and pulse fluctuation conditions, the gait conditions and the pain degree of the patient;
the step of determining the completion degree of standing walking of the patient in the current walking process according to the current walking video data of the patient comprises the following steps:
if the current walking video data of the patient is not empty and the pixel value of the current walking video data of the patient is smaller than the preset pixel value, respectively calculating the upper datum line change angle theta of the patient in the appointed time according to the following formula according to the current walking video data of the patient u And the lower datum line changes angle theta d ：
Wherein the saidAn upper datum line slope of a patient in the video data of the initial frame in the appointed time; the saidThe slope of the upper datum line of the patient in the last frame of video data in the appointed time is given; said->A lower baseline slope for the patient in the video data for the initial frame within the specified time,/a>A slope of a lower datum line of a patient in the last frame of video data in the appointed time; the upper reference line is a connecting line between the center of the neck of the patient and the centers of the left and right buttocks of the patient; the lower reference line is a line connecting the centers of the left and right buttocks of the patient and the centers of the left and right ankles of the patient;
changing the angle theta according to the upper datum line u And the lower datum line change angle theta d And determining the completion degree of standing and walking of the patient according to a preset completion degree judging rule.
2. The method of claim 1, wherein said integrating said blood pressure and pulse fluctuations, said gait condition and said pain level of said patient to determine whether said patient is able to discharge from a hospital comprises:
determining a fluctuation judgment factor according to the blood pressure and pulse fluctuation conditions and a preset fluctuation judgment corresponding relation;
determining a gait judgment factor according to the gait condition and a preset gait judgment corresponding relation;
determining a pain judging factor according to the pain degree and a preset pain judging corresponding relation;
determining the sum of the fluctuation judgment factor, the gait judgment factor and the pain judgment factor as an anesthesia degree value of the patient;
and judging that the patient can be discharged according to the anesthesia degree value being larger than a preset threshold value, or else, the patient cannot be discharged.
3. The method according to claim 1 or 2, wherein the determining the blood pressure and pulse wave conditions of the patient from the pre-operative and current blood pressure data and pulse data of the patient further comprises:
acquiring preoperative and current blood pressure data and pulse data of the patient through a patient management system;
and acquiring current walking video data of the patient and current facial image data of the patient through an image acquisition device.
4. The method of claim 1, wherein said determining the blood pressure and pulse fluctuations of the patient from pre-operative and current blood pressure data and pulse data of the patient comprises:
determining the blood pressure and pulse fluctuation coefficient of a patient according to the pre-operation and current blood pressure data and pulse data of the patient by the following formula:
wherein f represents the blood pressure and pulse fluctuation coefficient, P a Indicating the current blood pressure of the patient, P b Representing the pre-operative blood pressure of the patient, M a Representing the current pulse of the patient M b Representing the pre-operative pulse of the patient.
5. The method of claim 1, wherein the determining the degree of completion of standing walking in the patient's current walking process from the patient's current walking video data further comprises:
if the current walking video data of the patient is empty, determining that the patient cannot walk at all; if the pixel values of the current walking video data of the patient are all larger than or equal to the preset pixel values, the patient is determined to need to be assisted by others to walk.
6. The method of claim 1, wherein said determining the degree of completion of the patient squat back station start-up from the patient's current walking video data comprises:
if the current walking video data of the patient is empty, determining that the patient cannot stand up after squatting;
if the current walking video data of the patient is not empty, determining the starting completion degree of the squatting post-station of the patient according to the following formula based on the current walking video data of the patient:
d f ＝|d last -d first |
wherein said d first A vertical distance between the center of the left and right buttocks of the patient and the center of the left and right ankle of the patient in the initial frame video data in the appointed time; said d last The vertical distance between the center of the left hip and the right hip of the patient and the center of the left ankle and the right ankle of the patient in the last frame of video data in the appointed time is set; the fps is the shooting speed of the video data in the specified time; f is the total frame number of the video data in the appointed time; said d f A difference value of a vertical distance between the centers of the left and right buttocks of the patient and the centers of the left and right ankle of the patient in the specified time; the v is the movement speed of the buttocks of the patient in the vertical direction within the specified time;
and determining the starting completion degree of the squatting post-station of the patient according to the movement speed of the buttocks of the patient in the vertical direction within the appointed time.
7. The method of claim 1, wherein said determining the current pain level of the patient from the current facial image data of the patient comprises:
and determining the current pain degree of the patient according to the current facial image data of the patient and the trained facial recognition model.
8. A day operation discharge judgment device, characterized by comprising:
the first determining module is used for determining the blood pressure and pulse fluctuation condition of the patient according to the pre-operation and current blood pressure data and pulse data of the patient;
the second determining module is used for determining the current gait condition of the patient according to the current walking video data of the patient; the method is particularly used for: determining the completion degree of standing walking and the completion degree of starting a squatting post station in the current walking process of the patient according to the current walking video data of the patient; determining the current gait condition of the patient according to the standing walking completion degree and the squatting post-station starting completion degree of the patient respectively;
a third determining module for determining a current pain level of the patient from the current facial image data of the patient;
the comprehensive judging module is used for integrating the blood pressure and pulse fluctuation condition, the gait condition and the pain degree of the patient and judging whether the patient can be discharged;
wherein the second determining module is further configured to:
if the current walking video data of the patient is not empty and the pixel value of the current walking video data of the patient is smaller than the preset pixel value, respectively calculating the upper datum line change angle theta of the patient in the appointed time according to the following formula according to the current walking video data of the patient u And the lower datum line changes angle theta d ：
Wherein the saidAn upper datum line slope of a patient in the video data of the initial frame in the appointed time; the saidThe slope of the upper datum line of the patient in the last frame of video data in the appointed time is given; said->A lower baseline slope for the patient in the video data for the initial frame within the specified time,/a>A slope of a lower datum line of a patient in the last frame of video data in the appointed time; the upper reference line is a connecting line between the center of the neck of the patient and the centers of the left and right buttocks of the patient; the lower reference line is a line connecting the centers of the left and right buttocks of the patient and the centers of the left and right ankles of the patient;
changing the angle theta according to the upper datum line u And the lower datum line change angle theta d And determining the completion degree of standing and walking of the patient according to a preset completion degree judging rule.
9. A computer-assisted device comprising a processor, a memory and a computer program stored on the memory and capable of running on the processor, characterized in that the processor runs the computer program to implement the method according to any one of claims 1-7.
10. A computer readable storage medium having stored thereon a computer program, wherein the program is executed by a processor to implement the method of any of claims 1-7.
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