CN112542235A - Method and system for automatically monitoring turnover nursing working quality - Google Patents
Method and system for automatically monitoring turnover nursing working quality Download PDFInfo
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Abstract
The invention discloses a method and a system for automatically monitoring the turning nursing working quality, wherein the method comprises the following steps: setting the lying position of the patient and the maximum duration of the lying position; collecting a video and identifying facial features; determining a human lying position according to the facial features; calculating the time length of the patient in a lying position, and comparing the time length with the set maximum time length of the lying position; and determining whether to carry out turnover reminding or not according to the comparison result. The invention is not limited by the position of the patient lying in bed, can accurately judge different lying positions, can realize automatic recording and evaluation of turning-over nursing operation, and avoids the conditions of inaccurate and unreal data recording caused by subjective reasons.
Description
Technical Field
The invention relates to the technical field of nursing monitoring, in particular to a method and a system for automatically monitoring the turning nursing working quality.
Background
A common complication in long-term bedridden patients is pressure sores. Patients with stroke paralysis, spinal injuries, late-stage Parkinson's disease and the like can not turn over automatically, and pressure sores often occur. Pressure sores are the breakdown and necrosis of tissue caused by prolonged compression of body part tissue, blood circulation disorders, and loss of tissue nutrition that results in loss of normal function of the skin. Domestic related reports show that the incidence rate of pressure sores of patients in the neurology department can reach 30% -60%, and the incidence rate of the pressure sores of the patients lying in the bed for a long time in home care can reach 20% -50%. Pressure sores not only harm the health of patients, reduce the quality of life, and obviously increase the burden of caregivers, but also increase the medical expense.
Pressure sores can be prevented from occurring by good care. One simple and effective measure is to change the body position of the patient lying in bed on time and correctly, namely to turn the patient over at regular time. Therefore, the health department of 2010 ranks the assistance of turning over patients as one of basic nursing service items (trial) of inpatients, and becomes an important content of high-quality nursing services. Because the condition that nurses are not enough to compile is frequently stored in the ward, the turn-over time is reasonably arranged, so that the patient can be comfortable, the pressure sore is not increased, and the workload of nursing staff can be reduced. Omission or negligence in the turning-over nursing work is reduced, and the satisfaction of the patient is improved. At present, the nursing work still generally adopts the mode of manual record to track the execution condition of the turnover work, not only can the operation condition of the turnover be accurately recorded, but also the precious time of nurses is occupied by frequent records.
Therefore, if the turnover nursing work can be automatically monitored, reminded and evaluated, careless omission of the nursing work can be avoided, and the nursing quality is improved.
The application numbers are: 201721278896.5, the name is: the invention discloses a turnover monitoring device, and provides a RFID transmitting and reading device, which utilizes the characteristic of high dielectric constant of a human body to shield RFID signals of corresponding areas on a bed or clothes when the human body is in lying positions in different directions. By analyzing the RFID signal source, the time length of the patient in the lying position in each direction can be judged, and an alarm is given according to a set time threshold value. The judgment of the patient lying position in the mode depends on the specific RFID area shielded by the patient, and when the patient lying position is inconsistent with the specific RFID area or the shielding is incomplete, the accurate judgment cannot be obtained. When a patient wears the RFID clothes, discomfort is brought to the patient or the burden in nursing is increased. The invention can not realize the recording and evaluation of the turning nursing operation.
The application numbers are: 201510172068.2, the name is: the invention discloses an intelligent turning-over alarm system, and provides the intelligent turning-over alarm system. And when the controller does not receive information numbers from different pressure switches within the set alarm time, the controller sends out a turn-over alarm. The invention is similar to the former thinking, and the judgment of the patient lying position triggers the on-off of the pressure switch depending on the specific area of the patient on the bed. Therefore, when the patient lying position does not match the occupied area, the accurate judgment cannot be made. In addition, the adoption of the pressure sensing method can generate false alarm due to the influence of individual shape and weight. This approach requires a special mattress to be laid on the bed, which can affect the comfort of the patient for long periods of time. The invention can not realize the recording and evaluation of the turning nursing operation.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method and a system for automatically monitoring the turning nursing working quality, which can accurately judge different lying positions without being limited by the lying positions of patients.
In a first aspect of the present invention, a method for identifying a lying position of a human body is provided, which includes:
acquiring a patient video in real time;
identifying facial features of a patient in the patient video;
and determining the lying position of the human body according to the facial features.
Optionally, the identifying facial features of the patient in the patient video, wherein facial features are identified using a convolutional neural network model of edge computation.
Optionally, the human body lying position is determined according to the facial features, wherein the human body lying position is determined according to the spatial distribution of the facial features, and is any one of a horizontal lying position, a left side lying position and a right side lying position.
In a second aspect of the present invention, a method for identifying turning over of a human body is provided, which comprises:
adopting the method for identifying the human body lying position to identify the human body lying position;
and judging whether the turning-over happens or not through the identified change of the lying position of the human body of the same patient.
In a third aspect of the present invention, a method for automatically monitoring the quality of turn-over nursing work is provided, which comprises:
setting the lying position of the patient and the maximum duration of the lying position;
adopting the method for identifying the human body lying position to identify the lying position of the patient;
calculating the time length of the patient in a lying position, and comparing the time length with the set maximum time length of the lying position;
and determining whether to carry out turnover reminding or not according to the comparison result.
Optionally, the method further comprises monitoring the patient for turning, wherein whether the turning occurs is judged by the identified change of the lying position of the human body of the same patient;
when the turning-over action is monitored, the time of turning-over is recorded, and a video clip which is preset minutes before the time point is intercepted.
Optionally, whether to perform a turn-over reminding is determined according to the comparison result, wherein any one of an upcoming turn-over reminding, an immediate turn-over reminding and a turn-over delay reminding is performed according to the comparison result.
Optionally, the method further comprises: evaluating the turning nursing working quality;
and calculating the proportion of the turning-over delay operation and the total duration of the accumulated turning-over delay to form a turning-over nursing working quality report.
Optionally, the time length of the patient in a lying position is calculated, wherein each time the change of the lying position is detected, the current lying position start time is recorded, the time length of the current lying position is accumulated, and the time length of the lying position is accumulated until the next lying position is detected.
In a fourth aspect of the present invention, there is provided a system for identifying a lying position of a human body, comprising:
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in the patient video;
and the lying position identification module is used for determining the lying position of the human body according to the facial features.
In a fifth aspect of the present invention, there is provided a system for recognizing a turn-over of a human body, comprising:
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in the patient video;
a lying position identification module which determines the lying position of the human body according to the facial features;
and the turning-over identification module is used for judging whether the turning-over happens or not through the identified change of the lying position of the human body of the same patient.
In a sixth aspect of the present invention, a system for automatically monitoring the quality of turn-over nursing work comprises:
a setting module that sets a patient's lying position and a maximum length of time that the lying position is held;
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in the patient video;
a lying position identification module which determines the lying position of the human body according to the facial features;
the calculation and comparison module calculates the time length of the patient in a lying position according to the result of the lying position identification module and compares the calculated time length with the set maximum time length of the lying position;
and the judging module determines whether to carry out turnover reminding or not according to the comparison result of the calculating and comparing module.
Compared with the prior art, the embodiment of the invention has at least one of the following advantages:
(1) according to the method and the system, the clinostatism and the turnover of the patient are identified by adopting the video data collected by the camera, so that the method and the system are not limited by the position of the patient on a sickbed and are more accurate; furthermore, a non-contact video acquisition mode can bring better comfort to the patient and does not influence nursing operation of nurses on the patient;
(2) according to the method and the system, the clinostatism is analyzed in an edge calculation mode, and the clinostatism and the turnover can be judged without transmitting video data to the outside, so that the privacy of a patient is protected;
(3) the method and the system of the invention realize the automatic recording and evaluation of the turnover nursing work, reduce the manual recording time of nurses, and avoid the inaccurate and unreal data recording caused by subjective reasons;
(4) the method and the system automatically intercept the video of the specific time interval before turning over, retain the real data of the operation process, can better trace and analyze the operation flow of the turning over process, and improve the nursing quality.
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Embodiments of the invention are further described below with reference to the accompanying drawings:
FIG. 1 is a flowchart illustrating a method for identifying a lying position of a human body according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of identifying a turn over of a human body according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for automatically monitoring and evaluating the quality of turn-over care according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the present invention.
Fig. 1 is a flowchart of a method for identifying a lying position of a human body according to an embodiment of the present invention. Referring to fig. 1, the method for identifying the lying position of the human body in the embodiment includes the following steps:
s100, collecting a patient video in real time;
s200, identifying facial features of a patient in a patient video;
and S300, determining the lying position of the human body according to the facial features.
According to the embodiment of the invention, the patient lying position is judged by adopting the method of identifying the facial features by adopting the machine vision technology, and different lying positions can be accurately judged without being limited by the lying position of the patient.
In a preferred embodiment, the real-time capturing of the patient video in S100 can be performed by using an existing video capturing device, such as an RGB-D camera or a thermal camera, and this non-contact video capturing manner can bring better comfort to the patient and does not affect the nursing operation of the nurse on the patient.
In a preferred embodiment, the facial features of the patient in the patient video are identified in S200, and the facial features can be identified by using a convolutional neural network model with edge calculation. The convolutional neural Network model using edge computation may use the existing technologies, such as 3DDE (Face Alignment using a 3D deep-interpolated Network of Regression Trees), san (style Aggregated Network for Facial Landmark Detection), TS3 (human superior candidates house to left From partial Labeled Images for Facial Landmark Detection), and other human Face keypoint Detection models. In the embodiment, the clinostatism is analyzed in an edge calculation mode, and the clinostatism and the turnover can be judged without transmitting video data to the outside, so that the privacy of a patient is protected.
In particular, identifying facial features of the patient in the patient video includes, but is not limited to, eyebrow, eye, nose, mouth, jaw contours, and the like. These feature regions are marked by the face keypoint detection model as several points, for example, 68 points can be used to mark the eyebrow, eye, nose, mouth, and chin contours. The feature areas and the added facial features may also be marked with more points. The model further extracts the coordinates of each keypoint in three-dimensional space. When the patient lying position changes, the coordinates of the key points of the facial features in the three-dimensional space change.
In a preferred embodiment, the human body lying position is determined according to the facial features in S300, and the human body lying position can be determined according to the spatial distribution change of the facial features, and is any one of a horizontal lying position, a left lateral lying position and a right lateral lying position. The change of the spatial distribution of the facial features means that the coordinates of the facial key points in the three-dimensional space change along with the change of the lying position of the patient. The included angle between the curved surface formed by the facial features and the horizontal plane can be analyzed through space vector matrix operation. The lying position of the human body is judged to be any one of the horizontal position, the left side lying position and the right side lying position according to the preset angle range. For example, the horizontal position is-45 degrees to 45 degrees, the left lateral position is < -45 degrees, and the right lateral position is >45 degrees.
Fig. 2 is a flowchart of a method for identifying turning over of a human body according to an embodiment of the present invention. Referring to fig. 2, the method for identifying turning over of a human body in the embodiment includes the following steps:
s100, acquiring a patient video in real time, wherein the video is supposed to cover the face of the patient;
s200, identifying facial features of a patient in a patient video;
s300, determining the lying position of the human body according to the facial features;
and S400, judging whether the patient turns over or not through the identified change of the lying position of the human body of the same patient.
The above embodiments S100 to S300 of the present invention can be implemented by using the corresponding technology in the method for identifying the lying position of the human body as shown in fig. 1.
In the embodiment of the invention, the patient lying position is judged by adopting a method for identifying facial features, whether the patient is turned over or not is further judged through the change of the lying position, and no additional equipment is required to be added on the bed surface or the patient is required to wear specific clothes. Meanwhile, the information is collected in a non-contact way, so that the original state and comfort level of the patient lying in bed are not influenced.
Fig. 3 is a flowchart of a method for automatically monitoring and evaluating the quality of turn-over care according to an embodiment of the present invention. Referring to fig. 3, the method for automatically monitoring and evaluating the quality of turn-over care in the present embodiment may include the following steps:
s11, setting a turnover plan, including setting the lying position of the patient and the maximum time length for the lying position to be kept;
s12, acquiring a patient video in real time for the patient with the turning plan, and analyzing the clinostatism/turning;
s13, identifying facial features of the patient in the patient video;
s14, determining the lying position of the human body according to the facial features;
s15, calculating the time length of the patient in a lying position, and comparing the time length with the set maximum time length of the lying position;
and S16, determining whether to remind the user of turning over according to the comparison result.
In the above embodiment S11 of the present invention, a turning plan may be designed in advance in the system, and the setting of the turning plan is mainly based on the actual situation of the patient and may be performed according to the suggestions of the doctor or the professional caregiver.
The above embodiments S12 to S14 of the present invention can be implemented by using the corresponding technology in the method for identifying the lying position of the human body as shown in fig. 1.
In a preferred embodiment, the time length of the patient in a lying position is calculated in S16, wherein, each time the change of the lying position is detected, the current lying position start time is recorded, the time length of the current lying position is accumulated, and the time length of the lying position is accumulated until the next occurrence of the lying position is detected. Specifically, after each lying position is detected, the time of the lying position is recorded immediately until the lying position changes.
In a preferred embodiment, in S16, whether to perform a turn-over reminder is determined according to the comparison result, and specifically, any one of a turn-over-about reminder, an immediate turn-over reminder, and a turn-over delay reminder may be performed according to the comparison result, so as to help a nurse to more effectively schedule a turn-over nursing work for a patient in a ward.
The relationship between the comparison result and the turning-over reminding function can be as follows:
(1) if the calculated time length of the lying position does not exceed the set maximum time length of the lying position, and the calculated time length of the lying position is within the time range in which the reminding does not need to be sent, the reminding is not sent;
(2) if the calculated lying position time length is close to or exceeds the set lying position holding maximum time length, a prompt for turning over is sent; for example, when the current lying position time reaches N minutes before the lying position keeps the set time, a warning about turning over is sent until the set time is reached. Such as: n is an integer value of 15 to 30.
(3) If the calculated length of time of the lying position is very close to or equal to the set maximum length of time for maintaining the lying position, sending an immediate turn-over prompt; for example, within M minutes after the current lying position time length exceeds the lying position set time length, a warning about turning over is sent until M minutes. Such as: m is an integer value from 15 to 30.
(4) And if the calculated lying position time length exceeds the set lying position holding maximum time length, a turnover delay prompt is sent. For example, after the time length of the current lying position exceeds the set time length L minutes of the lying position, a turnover delay prompt is sent until the turnover action is detected.
In a specific implementation, the specific allowable time range N, M, L between the calculated length of time for the lying position of (1) - (4) and the set maximum length of time for the lying position to be kept may be set according to the actual situation of each patient. The above embodiments are merely illustrative and are not intended to limit the present invention.
In a preferred embodiment, the method for automatically monitoring and evaluating the turnover nursing working quality can further comprise monitoring the turnover of the patient on the basis of the embodiment shown in fig. 3, wherein whether the turnover occurs is judged through the identified change of the lying position of the human body of the same patient; for example, when the lying position of the patient is changed, the patient is considered to turn over, and if the lying position of the patient is not changed all the time, the patient is considered to not turn over. When the turning-over action is monitored, the time of turning-over is recorded, and a video clip which is preset minutes before the time point is intercepted. For example, in an embodiment, the preset time is an integer value between 1 and 3 minutes, that is, a video clip 1 to 3 minutes before the time point is intercepted, so as to monitor the whole process. The video of the specific time interval before turning over is automatically intercepted, the real data of the operation process is reserved, the operation flow of the turning over process can be traced and analyzed better, and the nursing quality is improved.
In a preferred embodiment, the method for automatically monitoring and evaluating the quality of turn-over care work may further include, based on the embodiment shown in fig. 3: and evaluating the turning nursing working quality. Specifically, the proportion of the turning-over delay operation and the total duration of the turning-over delay are calculated to form a turning-over nursing working quality report.
In a preferred embodiment, the method for automatically monitoring and evaluating the turnover nursing working quality further comprises the following steps: when the change of the lying position is detected, the start time of the lying position is recorded, the time length of the current lying position is accumulated, and the time length of the lying position is accumulated until the change of the next lying position is detected.
The embodiment of the method for automatically monitoring and evaluating the turning nursing work quality realizes the automatic recording and evaluation of the turning nursing work, generates the quality report, reduces the manual recording time of nurses, and avoids the conditions of inaccurate and unreal data recording caused by subjective reasons.
Corresponding to the method of the embodiment shown in fig. 1, an embodiment of the present invention further provides a system for identifying a lying position of a human body, including:
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in a patient video;
and the lying position identification module is used for determining the lying position of the human body according to the facial features.
Corresponding to the method of the embodiment shown in fig. 2, an embodiment of the present invention further provides a system for identifying a turn-over of a human body, including:
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in a patient video;
a lying position identification module which determines the lying position of the human body according to the facial features;
and the turning-over identification module judges whether the turning-over happens or not through the identified change of the lying position of the human body of the same patient.
Corresponding to the method of the embodiment shown in fig. 3, in another embodiment of the present invention, a system for automatically monitoring the quality of turn-over care work includes:
a setting module that sets a patient's lying position and a maximum length of time that the lying position is held;
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in a patient video;
a lying position identification module which determines the lying position of the human body according to the facial features;
the calculation and comparison module calculates the time length of the patient in a lying position according to the result of the lying position identification module and compares the time length with the set maximum time length of the lying position;
and the judging module determines whether to carry out turnover reminding or not according to the comparison result of the calculating and comparing module.
Each module in the system can be realized by adopting the technology in the corresponding method, and the details are not repeated herein. Meanwhile, the above-mentioned various preferable technical features may be used in any combination without conflict with each other.
In order to better illustrate the above embodiments of the present invention, the following description is given with reference to a specific application example, but the following example is not intended to limit the present invention.
In the embodiment, the RGB-D camera or the thermal camera is used for collecting the video data of the patient in real time, and the face features of the patient are detected by the computer vision technology to monitor the lying position of the patient. When the patient keeps the same lying position and reaches the set time, a turn-over reminding is sent to the nursing staff. When the turning over of the patient is detected, the turning over operation time is automatically recorded, and a video of the turning over process is intercepted. And giving an evaluation result according to the delay time of the actual turning operation. Specifically, the following steps can be referred to:
step 1: and setting a turning plan of the patient in the ward. Nurses set care plans for patients in the ward to turn over, including the maximum length of time the patient is in the recumbent position and in the recumbent position.
Step 2: the patient is monitored for turning over. And for the patient with the turning plan, starting an RGB-D camera or a thermal camera for real-time monitoring, and continuously acquiring the lying video of the patient for analyzing the lying position and turning.
And step 3: detecting the lying position and the turning over of the patient. The patient bed-lying video collected by the RGB-D camera or the thermal sensing camera adopts a convolutional layer neural network model of edge calculation to identify the facial features of the patient. And determining the lying positions of the patient to be a horizontal position, a left side lying position and a right side lying position according to the spatial distribution condition of the facial features. The turning of the patient is judged by the change of different lying positions of the patient.
And 4, step 4: and calculating the time length of the lying position. And when the current lying position of the patient is detected, recording the starting time of the lying position, and accumulating the duration of the current lying position. The length of time of lying position is accumulated until the turning-over action of the patient is detected.
And 5: and (5) reminding the patient of turning over. To help nurses to more effectively arrange patients in the ward to turn over and care. Three turnover reminding modes are designed, namely, the turnover reminding mode is about to be used, the instant turnover reminding mode is used, and the turnover delay reminding mode is used.
And 5.1, reminding the user of turning over. And sending out a prompt of turning over till the set time length is reached when the current time length of the lying position reaches N minutes before the time length of the lying position is kept for the set time length. N is an integer value of 15 to 30.
And 5.2, immediately turning over to remind. And sending out a prompt of turning over till M minutes after the current lying position time length exceeds the lying position set time length. M is an integer value from 15 to 30.
And 5.3, turning-over delay reminding. And sending a turnover delay prompt after the current lying position time length exceeds the lying position set time length for L minutes until the turnover action is detected. L is an integer value from 15 to 30.
Step 6: and recording the turning-over operation. When the turning-over action of the patient is detected, the time of turning-over is recorded, and meanwhile, a video clip X minutes before the time point is intercepted and sent to a server for storage. X is an integer value of 1 to 3.
And 7: and evaluating the turning nursing working quality. And calculating the proportion of the turning delay operation of each patient, and accumulating the total turning delay time to form a ward turning quality report.
The method and the system for automatically monitoring the turning nursing working quality in the embodiment of the invention are not limited by the lying position of the patient, and can accurately judge different lying positions. Automatic recording and evaluation of turning-over nursing operation can be realized, and the conditions of inaccurate and unreal data recording caused by subjective reasons are avoided; the video in a specific time interval before turning over is automatically intercepted, the real data of the operation process is reserved, the operation flow of the turning over process can be traced and analyzed better, and the nursing quality is improved.
It should be noted that, the steps in the method provided by the present invention may be implemented by using corresponding modules, devices, units, and the like in the system, and those skilled in the art may refer to the technical solution of the system to implement the step flow of the method, that is, the embodiment in the system may be understood as a preferred example for implementing the method, and details are not described herein.
Those skilled in the art will appreciate that, in addition to implementing the system and its various devices provided by the present invention in purely computer readable program code means, the method steps can be fully programmed to implement the same functions by implementing the system and its various devices in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices thereof provided by the present invention can be regarded as a hardware component, and the devices included in the system and various devices thereof for realizing various functions can also be regarded as structures in the hardware component; means for performing the functions may also be regarded as structures within both software modules and hardware components for performing the methods.
The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, and not to limit the invention. Any modifications and variations within the scope of the description, which may occur to those skilled in the art, are intended to be within the scope of the invention.
Claims (13)
1. A method of identifying a lying position of a human body, comprising:
acquiring a patient video in real time;
identifying facial features of a patient in the patient video;
and determining the lying position of the human body according to the facial features.
2. The method of claim 1, wherein the identifying facial features of the patient in the patient video is performed using a convolutional neural network model with edge computation.
3. The method of claim 2, wherein the identifying facial features of the patient in the patient video comprises eyebrow, eye, nose, mouth, and chin contours.
4. The method for identifying the human body lying position according to claim 1, wherein the human body lying position is determined according to the facial features, wherein the human body lying position is determined according to the spatial distribution of the facial features, and is any one of a horizontal lying position, a left side lying position and a right side lying position.
5. A method of identifying a turn-over in a human, comprising:
identifying a lying position of a human body by using the method of any one of claims 1 to 4;
and judging whether the turning-over happens or not through the identified change of the lying position of the human body of the same patient.
6. A method for automatically monitoring the turnover nursing working quality is characterized by comprising the following steps:
setting the lying position of the patient and the maximum duration of the lying position;
identifying the patient's lying position using the method of any one of claims 1-4;
calculating the time length of the patient in a lying position, and comparing the time length with the set maximum time length of the lying position;
and determining whether to carry out turnover reminding or not according to the comparison result.
7. The method for automatically monitoring the quality of turn-over care work according to claim 6, further comprising monitoring the turn-over of a patient, wherein the turn-over is judged whether or not by the identified change of the lying position of the human body of the same patient;
when the turning-over action is monitored, the time of turning-over is recorded, and a video clip which is preset minutes before the time point is intercepted.
8. The method for automatically monitoring the work quality of turn-over nursing according to claim 6, wherein the determination of whether to perform turn-over reminding is performed according to the comparison result, wherein any one of the prompt of about to turn over, the prompt of immediately turning over and the prompt of delay of turning over is performed according to the comparison result.
9. The method for automatically monitoring the quality of turn-over care work of claim 6, further comprising: evaluating the turning nursing working quality;
and calculating the proportion of the turning-over delay operation and the total duration of the accumulated turning-over delay to form a turning-over nursing working quality report.
10. The method for automatically monitoring the work quality of turning over nursing care of claim 6, wherein the time length of the patient in a lying position is calculated, wherein each time the change of the lying position is detected, the start time of the current lying position is recorded, the time length of the current lying position is accumulated, and the time length of the lying position is accumulated until the next lying position is detected.
11. A system for identifying a lying position of a human body, comprising:
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in the patient video;
and the lying position identification module is used for determining the lying position of the human body according to the facial features.
12. A system for identifying a turn in a human body, comprising:
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in the patient video;
a lying position identification module which determines the lying position of the human body according to the facial features;
and the turning-over identification module is used for judging whether the turning-over happens or not through the identified change of the lying position of the human body of the same patient.
13. A system for automatically monitoring the quality of turn-over nursing work, which is characterized by comprising:
a setting module that sets a patient's lying position and a maximum length of time that the lying position is held;
a collection module that collects patient video in real time;
a facial feature recognition module that recognizes facial features of a patient in the patient video;
a lying position identification module which determines the lying position of the human body according to the facial features;
the calculation and comparison module calculates the time length of the patient in a lying position according to the result of the lying position identification module and compares the calculated time length with the set maximum time length of the lying position;
and the judging module determines whether to carry out turnover reminding or not according to the comparison result of the calculating and comparing module.
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| CN202011490726.XA CN112542235A (en) | 2020-12-17 | 2020-12-17 | Method and system for automatically monitoring turnover nursing working quality |
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