CN109324188B - Accurate dynamic urine measurement method and system - Google Patents
Accurate dynamic urine measurement method and system Download PDFInfo
- Publication number
- CN109324188B CN109324188B CN201811185343.4A CN201811185343A CN109324188B CN 109324188 B CN109324188 B CN 109324188B CN 201811185343 A CN201811185343 A CN 201811185343A CN 109324188 B CN109324188 B CN 109324188B
- Authority
- CN
- China
- Prior art keywords
- urine
- data
- weighing
- specific gravity
- transmitter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 210000002700 urine Anatomy 0.000 title claims abstract description 116
- 238000000691 measurement method Methods 0.000 title description 4
- 238000005259 measurement Methods 0.000 claims abstract description 42
- 238000012360 testing method Methods 0.000 claims abstract description 40
- 238000013135 deep learning Methods 0.000 claims abstract description 26
- 230000005540 biological transmission Effects 0.000 claims abstract description 25
- 238000000034 method Methods 0.000 claims abstract description 19
- 238000001514 detection method Methods 0.000 claims abstract description 15
- 238000005303 weighing Methods 0.000 claims description 39
- 230000005484 gravity Effects 0.000 claims description 36
- 230000006870 function Effects 0.000 claims description 21
- 238000013499 data model Methods 0.000 claims description 11
- 230000008569 process Effects 0.000 claims description 8
- 238000012821 model calculation Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000011478 gradient descent method Methods 0.000 claims description 3
- 238000010561 standard procedure Methods 0.000 claims description 3
- 238000007670 refining Methods 0.000 claims 1
- 238000012886 linear function Methods 0.000 description 8
- 238000012544 monitoring process Methods 0.000 description 6
- 230000003907 kidney function Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- DDRJAANPRJIHGJ-UHFFFAOYSA-N creatinine Chemical compound CN1CC(=O)NC1=N DDRJAANPRJIHGJ-UHFFFAOYSA-N 0.000 description 2
- 238000013480 data collection Methods 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 229940109239 creatinine Drugs 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 210000002216 heart Anatomy 0.000 description 1
- 230000004217 heart function Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 239000002244 precipitate Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/62—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving urea
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Chemical & Material Sciences (AREA)
- Hematology (AREA)
- Immunology (AREA)
- Urology & Nephrology (AREA)
- Cell Biology (AREA)
- Microbiology (AREA)
- Biotechnology (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention discloses a method and a system for accurately and dynamically measuring urine, and relates to the technical field of medical detection. The accurate dynamic urine measuring system integrates a plurality of detection modules, carries out omnibearing measurement on urine to be measured, quickly converts the physical characteristics of the urine into electric signals to be transmitted into a urine memory to be stored, can control elements contained in each measurement module before and after the urine measurement through a control processor, can carry out wireless transmission on the physical characteristic information of the urine stored in the urine information memory through a wireless signal transmitter, can remotely transmit data to the urine information memory before the urine measurement through a wireless signal receiver, and can also remotely transmit signals to the control processor to carry out remote control on the urine measurement; meanwhile, the relationship between the output data of each sensor and the test result is simulated by adopting a deep learning-based method, so that the test result is comprehensive and accurate.
Description
Technical Field
The invention relates to the technical field of medical detection, in particular to a method and a system for accurately and dynamically measuring urine.
Background
Urine flow is an important index reflecting dynamic balance of human body fluid and heart and kidney functions, accurate urine flow monitoring is helpful for judging the change of disease conditions and guiding the formulation of a treatment scheme, the urine flow monitoring is an important content in detecting various indexes of a patient, for a severe patient, the urine flow can usually indicate the disorder of the kidney functions before the rise of blood creatinine, but for the urine flow, the important parameter capable of reflecting the effective circulating blood volume of a human body and the kidney functions in time is long-term, the accuracy and timeliness of clinical monitoring are far from sufficient, and safe automatic monitoring is not mentioned. At present, the urine monitoring to severe patients in clinic is manual discontinuous static monitoring at home, the workload of nurses is increased, the waste of medical care energy is caused, the danger of urine contact pollution is increased, the phenomena of incapability of measuring on time, error recording and the like can also occur, delay or serious mistake can be caused for clinical judgment, when the current urine is generated and measured, the accuracy of urine measurement is difficult to guarantee, the urine sample cannot be rapidly detected due to overhigh specific gravity of the urine of patients, and precipitates are generated on the urine sample, so that the accuracy deviation of urine measurement is larger.
Disclosure of Invention
The invention aims to provide a precise dynamic urine measuring system, so as to solve the problems in the prior art.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the utility model provides an accurate dynamic urine measurement system, includes urine measurement end and control transmission end, the urine measurement end carries out parameter measurement to the urine that awaits measuring to give control transmission end with data transmission.
Preferably, the urine measuring end comprises a temperature detecting module, a weighing measuring module and a specific gravity measuring module, wherein the temperature detecting module is used for measuring the temperature of urine and transmitting temperature data, and the weighing measuring module is used for weighing the urine entering the system and transmitting weight data; the specific gravity testing module tests the specific gravity of the urine and transmits data.
Preferably, the temperature detection module comprises a temperature sensor and a temperature transmitter, and the temperature detection module measures the temperature of urine through the temperature sensor and converts the detected urine temperature into an electric signal through the temperature transmitter for transmission; the weighing and measuring module comprises a weighing sensor and a weighing transmitter, the weighing and measuring module is used for weighing the entered urine through the weighing sensor and converting the detected urine weight into an electric signal through the weighing transmitter for transmission; the specific gravity measuring module comprises a specific gravity sensor and a specific gravity transmitter, wherein the specific gravity measuring module measures the specific gravity of the entering urine through the specific gravity sensor and converts the detected weight of the urine into an electric signal through the specific gravity transmitter for transmission.
Preferably, the control transmission end comprises a control storage module and an information transmission module, the control storage module comprises a control processor and a urine information memory, the control storage module controls and adjusts elements required by the control processor when measuring the physical characteristics of urine, and the urine information memory stores data converted by a temperature transmitter, a weighing transmitter and a specific gravity transmitter; the information transmission module comprises a wireless signal receiver and a wireless signal transmitter, wherein the wireless signal receiver receives external information wirelessly, and the wireless signal transmitter transmits stored information wirelessly.
Another objective of the present invention is to provide a method for performing accurate dynamic urine measurement by using the above measurement system, which mainly comprises the following steps:
s1: data acquisition: collecting urine data by adopting an independently developed accurate dynamic urine measurement system;
s2, establishing a data model: deep learning is carried out by adopting the data collected in the step S1, and a data model is established;
s3: and (3) data detection: and analyzing and detecting the urine data by using the data model established in the step S2.
Preferably, the data collection in step S1 is performed by measuring urine mainly using a sensor in the measuring system, wherein the sensor includes at least one of a weighing sensor, a temperature sensor and a specific gravity sensor, and the collected data is output data of the instrument.
Preferably, step S2 includes the steps of:
s21: data division: dividing the data collected in the step S1 into a training set and a test set;
s22: and (3) data learning: creating a linear model, and performing deep learning by using the data in the training set collected in the step S21 to obtain parameters of the linear model;
s23: establishing a function: creating a cost function using the output data of the measurement system and the output data of step S22, with the value of the cost function determining when to stop the deep learning process; when the value of the cost function is the minimum value, the deep learning is finished, and the step is S24;
s24: and (3) testing and comparing: testing by using the data in the test set, and comparing the actual test result with an expected result obtained by model calculation;
s25: and (3) conveying and curing: and solidifying the trained model into a measuring system.
Preferably, taking a load cell as an example, deep learning is performed on the collected output data, and the linear model in step S22 may be represented as: y ═ w0+w1x1+w2x2，
Said w0Is intercept, w1And w2Is a parameter, said x1And x2Respectively output data of two different weighing sensors;
the deep learning in step S22 is performed by using a standard gradient descent method, so as to obtain parameters of the linear model.
Preferably, the cost function in step S23 is an index function for measuring the correlation between linear model parameters obtained by deep learning, and the value of the cost function is calculated to determine whether deep learning can be terminated and output linear function parameters, where the cost function in the present invention can be expressed as:
said y(i)Is actually measured data by a standard method;
the above-mentioned
When the value j (w) of the cost function is the minimum value, it indicates that the accurate value of the linear function parameter for deep learning is the highest, and the deep learning process can be terminated, and the linear model obtained at this time is output, and the process proceeds to step S24.
Preferably, in the step S24, the data in the test set is used for testing, the output data in the test set is substituted into the linear model for calculation, an expected result obtained by the model calculation is compared with the data of the actual test, if the variance is greater than 5%, it indicates that the expected result is not met, and the linear model fitting is unsuccessful, the operation returns to the step S1, the data of the urine is collected again, and the test and the comparison are performed for multiple times; on the contrary, if the obtained variance is less than 5%, it indicates that the fitting of the linear model is successful, and the process proceeds to step S25, where the linear model is converted into a form of computer code and is solidified into the device, thereby completing the data fitting output of one sensor.
It should be noted that the above measurement method can be applied to various sensors and various calculation models, including not only weighing sensors, temperature sensors and specific gravity sensors, but also other analysis sensors; the fitted model may also include a variety of data models, including linear function models, non-linear function models, and the like.
The invention has the beneficial effects that:
the accurate dynamic urine measuring system integrates various detection modules, comprehensively measures urine to be measured, quickly converts physical characteristics of the urine into electric signals, transmits the electric signals to the urine memory for storage, controls elements contained in each measurement module before and after the urine measurement through the control processor, wirelessly transmits physical characteristic information of the urine stored in the urine information memory through the wireless signal transmitter, remotely transmits data to the urine information memory before the urine measurement through the wireless signal receiver, and remotely transmits signals to the control processor to remotely control the urine measurement; meanwhile, the relationship between the output data of each sensor and the test result is simulated by adopting a deep learning-based method, so that the test result is comprehensive and accurate.
Drawings
FIG. 1 is a block diagram of a precision dynamic urine measurement system;
FIG. 2 is a flow chart of a method for accurate dynamic urine measurement.
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 should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
Examples
As shown in fig. 1, the embodiment provides a precision dynamic urine measurement system, which includes a urine measurement end and a control transmission end, wherein the urine measurement end includes a temperature detection module, a weighing measurement module and a specific gravity measurement module, the temperature detection module includes a temperature sensor and a temperature transmitter, and the temperature detection module measures the temperature of urine through the temperature sensor and converts the detected urine temperature into an electrical signal through the temperature transmitter for transmission; the weighing and measuring module comprises a weighing sensor and a weighing transmitter, the weighing and measuring module is used for weighing the entered urine through the weighing sensor and converting the detected urine weight into an electric signal through the weighing transmitter for transmission; the specific gravity measuring module comprises a specific gravity sensor and a specific gravity transmitter, wherein the specific gravity measuring module measures the specific gravity of the entering urine through the specific gravity sensor and converts the detected weight of the urine into an electric signal through the specific gravity transmitter for transmission.
The control transmission end comprises a control storage module and an information transmission module, the control storage module comprises a control processor and a urine information memory, the control storage module controls and adjusts elements required when the control processor measures the physical characteristics of urine, and the urine information memory converts electric signals converted by the temperature transmitter, the weighing transmitter and the specific gravity transmitter into data for storage; the information transmission module comprises a wireless signal receiver and a wireless signal transmitter, wherein the wireless signal receiver receives external information wirelessly, and the wireless signal transmitter transmits stored information wirelessly.
Another objective of the present invention is to provide a method for performing accurate dynamic urine measurement by using the above measurement system, which mainly comprises the following steps:
s1: collecting data, namely collecting urine data by adopting an independently researched and developed accurate dynamic urine measuring system;
s2, establishing a data model: deep learning is carried out by adopting the data collected in the step S1, and a data model is established;
s21: data division: dividing the output data collected in the step S1 into a training set and a test set;
s22: and (3) data learning: creating a linear model, and performing deep learning by using the data in the training set collected in the step S21 to obtain parameters of the linear model;
s23: establishing a function: creating a cost function using the output data of the measurement system and the output data of step S22, with the value of the cost function determining when to stop the deep learning process; when the value of the cost function is the minimum value, the deep learning is finished, and the step is S24;
s24: and (3) testing and comparing: testing by using the data in the test set, and comparing the actual test result with an expected result obtained by model calculation;
s25: and (3) conveying and curing: and solidifying the trained model into a measuring system.
S3: and (3) data detection: and analyzing and detecting the urine data by using the data model established in the step S2.
It is noted that the data collection in step S1 is mainly to measure urine by using a sensor in the measuring system, the sensor includes at least one of a weighing sensor, a temperature sensor and a specific gravity sensor, and the collected data is the output data of the instrument.
Taking a weighing sensor as an example, deep learning is performed on the collected output data, and the linear model in step S22 can be represented as: y ═ w0+w1x1+w2x2，
Said w0Is intercept, w1And w2Is a parameter, said x1And x2Respectively output data of two different weighing sensors;
the deep learning in step S22 is performed by using a standard gradient descent method, so as to obtain parameters of the linear model.
The cost function in step S23 is an index function for measuring the correlation between linear model parameters obtained by deep learning, and determines whether deep learning can be terminated by calculating a value of the cost function, and outputs linear function parameters, where the cost function in this embodiment may be expressed as:
said y(i)Is actually measured data by a standard method;
the above-mentioned
The data obtained by calculating the linear model from the output data in the step 1 is adopted, when the value J (W) of the cost function is the minimum value, the accurate value of the linear function parameter value of the deep learning is the highest, the deep learning process can be terminated, and the linear model obtained at the moment is output, and the step S24 is entered.
In the step S24, the data in the test set is used for testing, the output data in the test set is substituted into the linear model for calculation, the expected result obtained by the model calculation is compared with the data sum of the actual test, if the variance is more than 5%, the expected result is not met, and the linear model fitting is unsuccessful, the operation returns to the step S1, the data of the urine is collected again, and the test and the comparison are carried out for many times; on the contrary, if the obtained variance is less than 5%, it indicates that the fitting of the linear model is successful, and the process proceeds to step S25, where the linear model is converted into a form of computer code and is solidified into the device, thereby completing the data fitting output of one sensor.
It should be noted that this embodiment is only an example of a sensor, but the above measurement method can be applied to various sensors and various calculation models, including not only weighing sensors, temperature sensors, and specific gravity sensors, but also other analysis sensors; the fitted model may also include a variety of data models, including linear function models, non-linear function models, and the like.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
the accurate dynamic urine measuring system integrates various detection modules, comprehensively measures urine to be measured, quickly converts physical characteristics of the urine into electric signals, transmits the electric signals to the urine memory for storage, controls elements contained in each measurement module before and after the urine measurement through the control processor, wirelessly transmits physical characteristic information of the urine stored in the urine information memory through the wireless signal transmitter, remotely transmits data to the urine information memory before the urine measurement through the wireless signal receiver, and remotely transmits signals to the control processor to remotely control the urine measurement; meanwhile, the relationship between the output data of each sensor and the test result is simulated by adopting a deep learning-based method, so that the test result is comprehensive and accurate.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (2)
1. A method for accurate dynamic urine measurement is characterized in that an accurate dynamic urine measurement system is adopted, the accurate dynamic urine measurement system comprises a urine measurement end and a control transmission end, the urine measurement end carries out parameter measurement on urine to be measured and transmits data to the control transmission end; the urine measuring end comprises a temperature detecting module, a weighing measuring module and a specific gravity measuring module, the temperature detecting module is used for measuring the temperature of urine and transmitting temperature data, and the weighing measuring module is used for weighing the urine entering the system and transmitting weight data; the specific gravity testing module tests the specific gravity of the urine and transmits data;
the temperature detection module comprises a temperature sensor and a temperature transmitter, and the temperature detection module measures the temperature of urine through the temperature sensor and converts the detected urine temperature into an electric signal through the temperature transmitter for transmission; the weighing and measuring module comprises a weighing sensor and a weighing transmitter, the weighing and measuring module is used for weighing the entered urine through the weighing sensor and converting the detected urine weight into an electric signal through the weighing transmitter for transmission; the specific gravity measuring module comprises a specific gravity sensor and a specific gravity transmitter, wherein the specific gravity measuring module measures the specific gravity of the entering urine through the specific gravity sensor and converts the detected weight of the urine into an electric signal through the specific gravity transmitter for transmission;
the control transmission end comprises a control storage module and an information transmission module, the control storage module comprises a control processor and a urine information memory, the control storage module controls and adjusts elements required when the control processor measures the physical characteristics of urine, and the urine information memory converts electric signals converted by the temperature transmitter, the weighing transmitter and the specific gravity transmitter into data for storage; the information transmission module comprises a wireless signal receiver and a wireless signal transmitter, wherein the wireless signal receiver wirelessly receives external information, and the wireless signal transmitter wirelessly transmits stored information;
the method for carrying out accurate dynamic urine measurement by using the measuring system comprises the following steps:
s1: data acquisition: collecting urine data by adopting an independently developed accurate dynamic urine measurement system;
s2: establishing a data model: deep learning is carried out by adopting the data collected in the step S1, and a data model is established;
s3: and (3) data detection: analyzing and detecting the urine data by adopting the data model established in the step S2;
step S2 includes the following steps:
s21: data division: dividing the data collected in the step S1 into a training set and a test set;
s22: and (3) data learning: creating a linear model, and performing deep learning by using the data in the training set collected in the step S21 to obtain parameters of the linear model;
s23: establishing a function: creating a cost function using the actually measured data and the output data of step S22;
s24: and (3) testing and comparing: testing by using the data in the test set, and comparing the test result with an expected result obtained by model calculation;
s25: and (3) conveying and curing: solidifying the trained model into a measuring system;
the linear model in step S22 can be expressed as:
y＝w0+w1x1+w2x2，
said w0Is intercept, w1And w2Is a parameter, said x1And x2Respectively output data of two different weighing sensors;
the cost function in step S24 can be expressed as:
said y(i)Is actually measured data by a standard method;
the above-mentioned
Is the output data calculated by the linear model;
in the step S24, the data in the test set is used for testing, the output data in the test set is substituted into the linear model for calculation, the expected result obtained by the model calculation is compared with the data sum of the actual test, if the variance is more than 5%, the expected result is not met, and the linear model fitting is unsuccessful, the operation returns to the step S1, the data of the urine is collected again, and the test and the comparison are carried out for many times; on the contrary, if the obtained variance is less than 5%, it indicates that the fitting of the linear model is successful, and the process proceeds to step S25, where the linear model is converted into a form of computer code and is solidified into the device, thereby completing the data fitting output of one sensor.
2. The method for refining dynamic urine measurement according to claim 1, wherein the deep learning in step S22 is performed by using a standard gradient descent method, so as to obtain parameters of a linear model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811185343.4A CN109324188B (en) | 2018-10-11 | 2018-10-11 | Accurate dynamic urine measurement method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811185343.4A CN109324188B (en) | 2018-10-11 | 2018-10-11 | Accurate dynamic urine measurement method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109324188A CN109324188A (en) | 2019-02-12 |
| CN109324188B true CN109324188B (en) | 2022-04-08 |
Family
ID=65261295
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811185343.4A Active CN109324188B (en) | 2018-10-11 | 2018-10-11 | Accurate dynamic urine measurement method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109324188B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116058843B (en) * | 2023-03-13 | 2024-11-22 | 珠海沃姆电子有限公司 | A digital dynamic urine monitoring method and system |
| CN116481592A (en) * | 2023-04-17 | 2023-07-25 | 上海摩翮生物科技有限公司 | A reagent precision detection process method and system |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5769087A (en) * | 1993-11-12 | 1998-06-23 | Fresenius Ag | Urine measurement apparatus and method for the determination of the density of urine |
| CN101806697A (en) * | 2010-03-29 | 2010-08-18 | 爱普科学仪器（江苏）有限公司 | urine detector |
| CN102865912A (en) * | 2012-09-07 | 2013-01-09 | 珠海沃姆电子有限公司 | Dynamic urine monitor and dynamic urine monitoring instrument |
| CN103054589A (en) * | 2013-01-31 | 2013-04-24 | 科迈（常州）电子有限公司 | Urine volume dynamic monitoring system and method |
| CN103932720A (en) * | 2014-05-09 | 2014-07-23 | 珠海沃姆电子有限公司 | Method and system for measuring urine volume and urine flow rate |
| CN104756117A (en) * | 2012-10-25 | 2015-07-01 | 皇家飞利浦有限公司 | Combined use of clinical risk factors and molecular markers for thrombosis for clinical decision support |
| CN106845140A (en) * | 2017-03-01 | 2017-06-13 | 重庆工商大学 | A kind of kidney failure method for early warning monitored based on specific gravity of urine and urine volume and system |
| CN107037001A (en) * | 2017-06-15 | 2017-08-11 | 中国科学院半导体研究所 | A kind of corn monoploid seed discrimination method based on near-infrared spectrum technique |
| CN107908928A (en) * | 2017-12-21 | 2018-04-13 | 天津科技大学 | A kind of hemoglobin Dynamic Spectrum Analysis Forecasting Methodology based on depth learning technology |
| CN107966534A (en) * | 2017-12-25 | 2018-04-27 | 河北先河环保科技股份有限公司 | Toxic and harmful gas network monitor instrument and monitoring data processing method with sensor detecting element |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7474911B2 (en) * | 2005-06-07 | 2009-01-06 | Solulearn Learning Solutions Ltd. | System and method for monitoring the volume of urine within a bladder |
| US20150371151A1 (en) * | 2014-06-20 | 2015-12-24 | The Regents Of The University Of California | Energy infrastructure sensor data rectification using regression models |
| CN103598886B (en) * | 2013-11-28 | 2015-10-28 | 中山大学 | Based on the method for dynamic urine volume in the long-pending urine process of model compensation method monitoring |
| CA2994366C (en) * | 2015-08-05 | 2024-01-09 | Art Healthcare Ltd. | Point of care urine analyzer |
-
2018
- 2018-10-11 CN CN201811185343.4A patent/CN109324188B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5769087A (en) * | 1993-11-12 | 1998-06-23 | Fresenius Ag | Urine measurement apparatus and method for the determination of the density of urine |
| CN101806697A (en) * | 2010-03-29 | 2010-08-18 | 爱普科学仪器（江苏）有限公司 | urine detector |
| CN102865912A (en) * | 2012-09-07 | 2013-01-09 | 珠海沃姆电子有限公司 | Dynamic urine monitor and dynamic urine monitoring instrument |
| CN104756117A (en) * | 2012-10-25 | 2015-07-01 | 皇家飞利浦有限公司 | Combined use of clinical risk factors and molecular markers for thrombosis for clinical decision support |
| CN103054589A (en) * | 2013-01-31 | 2013-04-24 | 科迈（常州）电子有限公司 | Urine volume dynamic monitoring system and method |
| CN103932720A (en) * | 2014-05-09 | 2014-07-23 | 珠海沃姆电子有限公司 | Method and system for measuring urine volume and urine flow rate |
| CN106845140A (en) * | 2017-03-01 | 2017-06-13 | 重庆工商大学 | A kind of kidney failure method for early warning monitored based on specific gravity of urine and urine volume and system |
| CN107037001A (en) * | 2017-06-15 | 2017-08-11 | 中国科学院半导体研究所 | A kind of corn monoploid seed discrimination method based on near-infrared spectrum technique |
| CN107908928A (en) * | 2017-12-21 | 2018-04-13 | 天津科技大学 | A kind of hemoglobin Dynamic Spectrum Analysis Forecasting Methodology based on depth learning technology |
| CN107966534A (en) * | 2017-12-25 | 2018-04-27 | 河北先河环保科技股份有限公司 | Toxic and harmful gas network monitor instrument and monitoring data processing method with sensor detecting element |
Non-Patent Citations (2)
| Title |
|---|
| 基于尿常规的机器学习辅助泌尿系统肿瘤筛查;王正等;《泌尿外科杂志(电子版)》;20180630;第10卷(第2期);第13-16页 * |
| 自动连续监测尿液流量和电导率装置的研制;李祖国等;《西南国防医药》;20150930;第25卷(第9期);第935-938页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109324188A (en) | 2019-02-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103561636B (en) | Heating detection device | |
| CN104452926B (en) | A health monitoring system based on smart toilet | |
| EP1085534A3 (en) | Intelligent analysis system and method for fluid-filled electrical equipment | |
| US20170307423A1 (en) | System for automated measurement of fluid output | |
| EP1085635A3 (en) | Fluid-filled electrical equipment intelligent analysis system and method | |
| CN109324188B (en) | Accurate dynamic urine measurement method and system | |
| CN104220859B (en) | For testing the system of palm grip power | |
| CN103654798B (en) | Emotion monitoring and recording method and device | |
| CN204909419U (en) | Human physiology index detection device | |
| CN116660781A (en) | Outdoor high-power bidirectional quick-charging mobile power supply testing system | |
| CN106289578A (en) | A kind of temperature sensor intelligent checking system | |
| CN104840194A (en) | Digital electrocardiograph calibration method and system | |
| WO2011077275A3 (en) | Bode index measurement | |
| CN117607227B (en) | Real-time monitoring and abnormal warning method of electrolyte analyzer based on deep learning | |
| US20200370944A1 (en) | Pressure and temperature based scale | |
| CN115169986A (en) | A Quality Control System for Clinical Laboratory | |
| CN205585989U (en) | Combine high weight waistline measuring apparatu of fit | |
| CN202599900U (en) | Device for detecting hydroxide content of straight hair cream | |
| CN203772412U (en) | Desk type laser power meter capable of real-time compensation | |
| CN116481592A (en) | A reagent precision detection process method and system | |
| CN113689750A (en) | Scoring method and device, electronic equipment and readable medium | |
| CN102421355A (en) | Method for measuring blood oxygen of fingers and finger gripping oximeter | |
| CN213581870U (en) | Temperature acquisition device and pipeline temperature monitoring system | |
| CN201607381U (en) | High-precision weighing sensor applied to detection of residual deformation rate of hydrogen making cylinder | |
| CN104458843A (en) | Intelligent blood glucose tester for medical treatment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |