CN114121277A - Pressure sore prediction system and method - Google Patents
Pressure sore prediction system and method Download PDFInfo
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Abstract
The invention relates to the technical field of biomedical engineering, and discloses a pressure sore prediction system, which comprises: the data processing unit is used for calculating the pressure average value of the pressure data in the determined time period, and comparing and calculating the pressure average value with the pressure minimum value and the pressure maximum value set by the system to obtain a risk accumulation parameter; the risk coefficient generating unit is used for acquiring the physical condition of the patient, evaluating influence factors for different physical conditions, and performing weighted summation on the influence factors to obtain a risk coefficient; and the disease prediction unit is used for multiplying the risk accumulation parameters of each time period by the risk coefficients and continuously accumulating the multiplication results according to the time periods to obtain the pressure sore occurrence probability. The method has high prediction precision, solves the problems of poor prevention effect of pressure sore clinically, large individual difference, heavy workload and the like at present, and has important application value for accurate prevention of pressure sore in clinical medicine.
Description
Technical Field
The invention relates to the technical field of biomedical engineering, in particular to a pressure sore prediction system and a pressure sore prediction method, which can be used for accurately preventing and treating chronic diseases such as pressure sore and the like in clinical medicine.
Background
The pressure sore is skin and soft tissue ulceration necrosis caused by ischemia and anoxia due to long-term pressure and insufficient blood supply of local tissues of a body, and a series of complications can be caused seriously due to the skin and soft tissue ulceration necrosis, so that the life safety of a patient is threatened. Pressure sores not only increase nursing workload and nosocomial infection risks, but also delay the recovery of basic diseases of patients and prolong hospitalization time. Clinically, the treatment time is obviously prolonged after the pressure sore occurs, and the treatment cost is increased.
The pressure applied to the skin is a key factor causing pressure sores, which easily occur at the pressed part when the pressure is above a critical value for a period of time. In order to prevent pressure sores, medical staff clinically replace body positions at regular time (generally about 2 hours) and intermittently relieve body pressure. However, these methods are not only lack of accuracy, unable to be individualized according to the patient's condition, and poor in preventive effect, but also have a great workload for medical staff. Therefore, the existing pressure sore prevention means cannot meet the actual clinical needs, and a more accurate pressure sore prediction system and method are urgently needed.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: in order to solve the problem that the existing pressure sore prediction system and method are inaccurate, the invention provides the pressure sore prediction system and method, and solves the problems that the existing clinical pressure sore prevention effect is poor, the individual difference is large, the workload is heavy, and the like.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a pressure wound prediction system comprising:
the data processing unit is used for calculating the pressure average value of the pressure data in the determined time period, and comparing and calculating the pressure average value with the pressure minimum value and the pressure maximum value set by the system to obtain a risk accumulation parameter;
the risk coefficient generating unit is used for acquiring the physical condition of the patient, evaluating influence factors for different physical conditions, and performing weighted summation on the influence factors to obtain a risk coefficient;
and the disease prediction unit is used for multiplying the risk accumulation parameters of each time period by the risk coefficients and continuously accumulating the multiplication results according to the time periods to obtain the pressure sore occurrence probability.
Further, the pressure sore prediction system further comprises a pressure sensor, and the pressure sensor is arranged below a pressure sore prone position of a bedridden patient.
Further, in the data processing unit, the measured pressure data is cached, the cached pressure data is segmented according to a set fixed time interval, and the average value of the pressure is calculated as
In the formula, Pn,mFor pressure data, N is a pressure data serial number (N is 1,2,3, …, N) of a certain fixed time interval, and M is a fixed time period serial number (M is 1,2,3, …, M);
the minimum pressure value and the maximum pressure value are respectively set to be PminAnd PmaxAverage value of pressure and Pmin、PmaxComparing and calculating to obtain the risk accumulation parameter R of the mth section of fixed time intervalmComprises the following steps:
further, in the risk coefficient generating unit, the obtained physical condition of the patient includes age, body quality index and risk degree, and the influence factors corresponding to the age, the body quality index and the risk degree are respectively evaluated;
weighting and summing the corresponding influence factors of age, body quality index and risk degree to obtain a risk coefficient H:
H＝Aq1+Bq2+Cq3
in the formula, q1、q2、q3The influence factors corresponding to the age, the body quality index and the risk degree respectively, and A, B, C are weighted values of the age, the body quality index and the risk degree respectively, wherein
Further, in the disease prediction unit, the risk accumulation parameter of the mth segment of fixed time interval obtained by calculation is multiplied by the risk coefficient, and under the condition that the posture of the patient is not changed, the multiplication results obtained in different time segments are sequentially accumulated to obtain the pressure sore occurrence probability as follows:
and the occurrence probability of pressure sores is compared with the set early warning threshold, so that the risk of pressure sores is early warned in real time.
The invention also discloses a pressure sore prediction method, which comprises the following steps:
step S1, calculating the pressure average value of the pressure data in the determined time period, and comparing and calculating the pressure average value with the set pressure minimum value and pressure maximum value to obtain a risk accumulation parameter;
step S2, acquiring the physical condition of the patient, evaluating influence factors for different physical conditions, and performing weighted summation on the influence factors to obtain a risk coefficient;
and step S3, multiplying the risk accumulation parameters of each time period by the risk coefficients, and continuously accumulating the multiplication results according to the time periods to obtain the pressure sore occurrence probability.
Further, the pressure data acquisition method comprises the following steps: a pressure sensor is arranged below the pressure sore prone position of the bedridden patient.
Further, in step S1, the measured pressure data is buffered, the buffered pressure data is segmented according to the set fixed time interval, and the average value of the pressure is calculated as N pressure data of the mth segment at the fixed time interval
In the formula, Pn,mFor pressure data, N is a pressure data serial number (N is 1,2,3, …, N) of a certain fixed time interval, and M is a fixed time period serial number (M is 1,2,3, …, M);
the minimum pressure value and the maximum pressure value are respectively set to be PminAnd PmaxAverage value of pressure and Pmin、PmaxComparing and calculating to obtain the risk accumulation parameter R of the mth section of fixed time intervalmComprises the following steps:
further, in step S2, the obtained physical condition of the patient includes age, body quality index, and risk level, and the influence factors corresponding to the age, the body quality index, and the risk level are respectively evaluated;
weighting and summing the corresponding influence factors of age, body quality index and risk degree to obtain a risk coefficient H:
H＝Aq1+Bq2+Cq3
in the formula, q1、q2、q3The influence factors corresponding to the age, the body quality index and the risk degree respectively, and A, B, C are weighted values of the age, the body quality index and the risk degree respectively, wherein
Further, in step S3, the calculated risk accumulation parameter of the mth period of fixed time interval is multiplied by the risk coefficient, and under the condition that the posture of the patient does not change, the multiplication results obtained in different time periods are sequentially accumulated, so as to obtain the pressure sore occurrence probability as follows:
and the occurrence probability of pressure sores is compared with the set early warning threshold, so that the risk of pressure sores is early warned in real time.
Compared with the prior art, the invention has the following beneficial effects: the invention provides a pressure sore prediction system and a pressure sore prediction method. The method provided by the invention can realize accurate prediction of pressure sore occurrence aiming at different patients, has the advantages of high accuracy, good individual adaptability, simple and convenient clinical application and the like, and has important application value for accurate pressure sore prevention in clinical medicine.
Drawings
Fig. 1 is a block diagram of an overall implementation of the pressure wound prediction system of the present invention.
FIG. 2 is a block diagram of a data processing unit implementation of the present invention.
Fig. 3 is a block diagram of a disease prediction unit implementation of the present invention.
FIG. 4 is a block diagram of a risk coefficient generation implementation of the present invention.
FIG. 5 is a graph of the occurrence probability of pressure sores versus time in accordance with the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 shows a general implementation method of a pressure sore prediction system. The pressure sensor is placed below the pressure sore prone position of the bedridden patient and outputs measured pressure data according to a certain time period. And the pressure data enters a data processing unit, and the pressure data is calculated to obtain a risk accumulation parameter. The risk coefficient generating unit obtains a risk coefficient according to the input physical condition of the patient. And (4) the risk accumulation parameters and the risk coefficients enter a disease prediction unit, the pressure sore occurrence probability is calculated through the determined functional relation, and early warning is carried out according to the condition.
FIG. 2 illustrates a data processing unit implementing the method. The data processing unit receives and caches the measured pressure data, sets a time period, averages the data in segments according to a set fixed time interval, and calculates the average pressure value as N pressure data of the mth segment of the fixed time interval
In the formula, Pn,mFor the pressure data, N is a pressure data number (N is 1,2,3, …, N) of a certain fixed time interval, and M is a fixed time period number (M is 1,2,3, …, M).
The minimum pressure value and the maximum pressure value set by the processing unit are respectively PminAnd PmaxAverage value of pressure and Pmin、PmaxComparing and calculating to obtain the risk accumulation parameter R of the mth section of fixed time intervalmComprises the following steps:
fig. 3 is a block diagram of a risk coefficient generation unit implementation. The physical condition of the patient (the age, body mass index, risk level of the patient) is obtained, and the influence factors are respectively evaluated according to the age, body mass index, risk level of the patient, and one embodiment of the generation of the influence factors is shown in table 1.
TABLE 1
| Age (age) | Influencing factor | Body mass index | Influencing factor | Degree of danger | Influencing factor |
| <Age 21 | 0 | 20-24.9 | 0.25 | Is low in | 0.25 |
| 21-40 years old | 0.25 | 25-29.1 | 0.5 | In | 0.5 |
| Age 41-60 | 0.5 | >30 | 0.75 | Height of | 0.75 |
| 61-80 years old | 0.75 | <20 | 1 | Super high | 1 |
| >Age 81 | 1 |
The risk coefficient is obtained by weighted summation of the three influence factors:
H＝Aq1+Bq2+Cq3 (3)
in the formula, q1、q2、q3The influence factors corresponding to age, body mass index and risk degree are respectively, and A, B, C are respectively weighted values.
According to the age, the body quality index and the contribution of the risk degree of the patient to the occurrence of the pressure sore, the weighted value is obtained as follows:
fig. 4 is a block diagram of a disease prediction unit implementation. Multiplying the risk accumulation parameters of the m-th time interval by the risk coefficients, summing in sections under the condition that the posture of the patient is not changed, sequentially accumulating the product results obtained in different time intervals to obtain the pressure sore occurrence probability as follows:
through the comparison of the pressure sore occurrence probability and the set early warning threshold, the early warning can be carried out on the pressure sore onset risk in real time.
The following further illustrates the performance and features of the present invention by way of example of an actual patient. The age of a patient is 70 years, the body quality index is 27, the risk degree index is middle, the pressure measurement period for the sacrococcygeal region is 1s, the output period of the pressure sore occurrence probability is 2min, and under the condition that the posture is kept unchanged, the time-varying relation of the pressure sore occurrence probability of the part can be obtained through simulation calculation as shown in fig. 5. When the time is about 80min, the pressure sore occurrence probability reaches 0.5, and if the set early warning threshold is 0.5, the system needs to remind the patient to adjust the posture.
Finally, it should be noted that: the above embodiments are only preferred embodiments of the present invention to illustrate the technical solutions of the present invention, but not to limit the technical solutions, and certainly not to limit the patent scope of the present invention; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention; that is, the technical problems to be solved by the present invention, which are not substantially changed or supplemented by the spirit and the concept of the main body of the present invention, are still consistent with the present invention and shall be included in the scope of the present invention; in addition, the technical scheme of the invention is directly or indirectly applied to other related technical fields, and the technical scheme is included in the patent protection scope of the invention.
Claims (10)
1. A pressure wound prediction system, comprising:
the data processing unit is used for calculating the pressure average value of the pressure data in the determined time period, and comparing and calculating the pressure average value with the pressure minimum value and the pressure maximum value set by the system to obtain a risk accumulation parameter;
the risk coefficient generating unit is used for acquiring the physical condition of the patient, evaluating influence factors for different physical conditions, and performing weighted summation on the influence factors to obtain a risk coefficient;
and the disease prediction unit is used for multiplying the risk accumulation parameters of each time period by the risk coefficients and continuously accumulating the multiplication results according to the time periods to obtain the pressure sore occurrence probability.
2. The pressure wound prediction system of claim 1 further comprising a pressure sensor disposed below a pressure wound prone site of a bedridden patient.
3. The pressure wound prediction system of claim 1 wherein the data processing unit buffers the measured pressure data, segments the buffered pressure data according to a set fixed time interval, and calculates an average of the pressures for the N pressure data for the mth fixed time interval as:
in the formula, Pn,mFor pressure data, N is a pressure data serial number of a certain fixed time interval, N is 1,2,3, …, N, M is a fixed time period serial number, and M is 1,2,3, …, M;
the minimum pressure value and the maximum pressure value are respectively set to be PminAnd PmaxAverage value of pressure and Pmin、PmaxComparison meterCalculating to obtain a risk accumulation parameter R of the m-th fixed time intervalmComprises the following steps:
4. the pressure wound prediction system of claim 3 wherein in the risk factor generation unit, the obtained physical condition of the patient includes age, body quality index, risk level, and the influence factors corresponding to the age, body quality index, risk level are evaluated respectively;
weighting and summing the corresponding influence factors of age, body quality index and risk degree to obtain a risk coefficient H:
H＝Aq1+Bq2+Cq3
in the formula, q1、q2、q3The influence factors corresponding to the age, the body quality index and the risk degree respectively, and A, B, C are weighted values of the age, the body quality index and the risk degree respectively, wherein
5. The pressure sore prediction system of claim 4 wherein the disease prediction unit multiplies the calculated risk accumulation parameter for the mth fixed time interval by the risk factor, and sequentially adds the product results obtained for different time intervals without changing the posture of the patient to obtain a pressure sore occurrence probability of:
and the occurrence probability of pressure sores is compared with the set early warning threshold, so that the risk of pressure sores is early warned in real time.
6. A method of pressure wound prediction, comprising:
step S1, calculating the pressure average value of the pressure data in the determined time period, and comparing and calculating the pressure average value with the set pressure minimum value and pressure maximum value to obtain a risk accumulation parameter;
step S2, acquiring the physical condition of the patient, evaluating influence factors for different physical conditions, and performing weighted summation on the influence factors to obtain a risk coefficient;
and step S3, multiplying the risk accumulation parameters of each time period by the risk coefficients, and continuously accumulating the multiplication results according to the time periods to obtain the pressure sore occurrence probability.
7. The pressure wound prediction method of claim 1 wherein the pressure data acquisition method is: a pressure sensor is arranged below the pressure sore prone position of the bedridden patient.
8. The pressure wound prediction method of claim 6, wherein in step S1, the measured pressure data is buffered, the buffered pressure data is segmented according to a set fixed time interval, and the average value of the pressures is calculated as N pressure data for the mth fixed time interval
In the formula, Pn,mFor pressure data, n is pressure data for a fixed time intervalN, 3, …, M is a fixed time period number, M is 1,2,3, …, M;
the minimum pressure value and the maximum pressure value are respectively set to be PminAnd PmaxAverage value of pressure and Pmin、PmaxComparing and calculating to obtain the risk accumulation parameter R of the mth section of fixed time intervalmComprises the following steps:
9. the pressure wound prediction method of claim 8, wherein in step S2, the obtained physical condition of the patient includes age, body quality index, and risk level, and the respective evaluation results show the corresponding influence factors of age, body quality index, and risk level;
weighting and summing the corresponding influence factors of age, body quality index and risk degree to obtain a risk coefficient H:
H＝Aq1+Bq2+Cq3
in the formula, q1、q2、q3The influence factors corresponding to the age, the body quality index and the risk degree respectively, and A, B, C are weighted values of the age, the body quality index and the risk degree respectively, wherein
10. The pressure sore prediction method of claim 9 wherein in step S3, the calculated risk accumulation parameters for the m-th fixed time interval are multiplied by risk coefficients, and the multiplication results obtained for different time intervals are sequentially added without changing the posture of the patient, so as to obtain a pressure sore occurrence probability of:
and the occurrence probability of pressure sores is compared with the set early warning threshold, so that the risk of pressure sores is early warned in real time.
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| CN117392117A (en) * | 2023-12-04 | 2024-01-12 | 四川省医学科学院·四川省人民医院 | Pressure sore detection method based on OpenCV image processing |
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| CN117392117A (en) * | 2023-12-04 | 2024-01-12 | 四川省医学科学院·四川省人民医院 | Pressure sore detection method based on OpenCV image processing |
| CN117392117B (en) * | 2023-12-04 | 2024-02-13 | 四川省医学科学院·四川省人民医院 | Pressure sore detection method based on OpenCV image processing |
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