CN117649909B - Optimized matching method for biomedical clinical test - Google Patents
Optimized matching method for biomedical clinical test Download PDFInfo
- Publication number
- CN117649909B CN117649909B CN202410115717.4A CN202410115717A CN117649909B CN 117649909 B CN117649909 B CN 117649909B CN 202410115717 A CN202410115717 A CN 202410115717A CN 117649909 B CN117649909 B CN 117649909B
- Authority
- CN
- China
- Prior art keywords
- test
- subgroup
- testers
- tester
- period
- 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
- 238000012360 testing method Methods 0.000 title claims abstract description 602
- 238000000034 method Methods 0.000 title claims abstract description 18
- 239000003814 drug Substances 0.000 claims abstract description 113
- 229940079593 drug Drugs 0.000 claims abstract description 58
- 238000004458 analytical method Methods 0.000 claims abstract description 37
- 238000012544 monitoring process Methods 0.000 claims description 54
- 230000036760 body temperature Effects 0.000 claims description 48
- 206010000117 Abnormal behaviour Diseases 0.000 claims description 41
- 230000002159 abnormal effect Effects 0.000 claims description 33
- 230000000877 morphologic effect Effects 0.000 claims description 18
- 230000006399 behavior Effects 0.000 claims description 12
- 238000007405 data analysis Methods 0.000 claims description 3
- 230000007717 exclusion Effects 0.000 claims description 3
- 230000037396 body weight Effects 0.000 claims 1
- 230000007547 defect Effects 0.000 abstract description 4
- 230000000857 drug effect Effects 0.000 description 4
- 238000012216 screening Methods 0.000 description 3
- 206010067484 Adverse reaction Diseases 0.000 description 2
- 230000006838 adverse reaction Effects 0.000 description 2
- 238000012106 screening analysis Methods 0.000 description 2
- 206010038776 Retching Diseases 0.000 description 1
- 206010044565 Tremor Diseases 0.000 description 1
- 206010047700 Vomiting Diseases 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002547 new drug Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000008673 vomiting Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Abstract
The invention relates to the technical field of medicine tests, in particular to an optimized matching method for a biomedical clinical test. Dividing the testers into test subgroups corresponding to the test groups based on the ages and the weights of the testers, not only making up the defects of the prior art on the age groups and the weight analysis tests of the testers, but also meeting the requirement on carrying out proper dose tests on the testers under the safety condition, further analyzing the temperature state indexes, the mind state indexes and the drug repulsion indexes of the testers corresponding to the test subgroups in the test groups to obtain the drug action values of the testers corresponding to the test subgroups in the test groups, further obtaining proper doses of the biomedicine corresponding to the weight grades in the age groups based on the analysis, comprehensively considering the influence of all aspects on the drug action values, avoiding the influence of individual differences on the drug action values to a great extent, and eliminating the problem of low dose invalidation or high dose harm to human bodies of the biomedicine.
Description
Technical Field
The invention relates to the technical field of medicine tests, in particular to an optimized matching method for a biomedical clinical test.
Background
Clinical trials of biological medicine are not only key stages in verifying the safety and effectiveness of biological medicine products, but also key steps in the development and innovation of new drugs. The test of the proper dosage of the biological medicine can effectively ensure the safety and the effectiveness in the real clinical situation, and the biological medicine clinical test needs to be optimally matched and analyzed in view of the safety and the effectiveness.
The existing clinical test of biological medicine not only ignores the absorption difference of testers at all ages on the drug effect of biological medicine, so that the accurate measurement of the drug effect is difficult. Meanwhile, the influence of the weight difference on the drug effect is ignored, so that the clinical test result of the drug has one-sided property and difference, and the stable exertion of the drug effect of the biological medicine is not facilitated.
Disclosure of Invention
Aiming at the technical defects, the invention aims to provide an optimized matching method for a biomedical clinical test.
The aim of the invention can be achieved by the following technical scheme: an optimized matching method for a biomedical clinical test comprises the following steps of;
S1, test group allocation: the method comprises the steps of obtaining ages of testers in a set age range, matching the ages of the testers with age thresholds corresponding to the set age ranges to obtain age ranges corresponding to the testers, classifying and sorting the testers according to the same age ranges to obtain the testers in the age ranges, and taking the testers as test groups.
S2, the test sub-components are distributed: the weight of each tester in each test group is obtained, and each test group is divided into test subgroups based on the weight of each tester in each test group, so that each test subgroup corresponding to each test group is obtained.
Preferably, each test group is divided into test subgroups based on the weight of each tester in each test group, in a specific manner: and matching the weight of each tester in each test group with the weight section corresponding to the set weight grade to obtain the weight grade of each tester in each test group, and dividing the testers with different weight grades according to the number of testers in the set reference test subgroup to obtain each tester in each test subgroup.
S3, dose test analysis: and acquiring a safety dose interval corresponding to the biological medicine, setting a plurality of test doses based on the safety dose interval corresponding to the biological medicine to obtain each test dose corresponding to the biological medicine, and performing a dose test on each test subgroup corresponding to each test subgroup according to each test dose corresponding to the biological medicine to obtain the test dose corresponding to each test subgroup in each test subgroup.
S4, basic data analysis: the method comprises the steps of collecting body temperature sets and heart rate sets of testers corresponding to test subgroups in test groups in a set period, analyzing the body temperature sets of testers corresponding to the test subgroups in the test groups in the set period to obtain the temperature state indexes of testers corresponding to the test subgroups in the test groups in the set period, and analyzing the heart rate sets of testers corresponding to the test subgroups in the test groups in the set period to obtain the heart state indexes of testers corresponding to the test subgroups in the test groups in the set period.
Preferably, the body temperature set and the heart rate set of each tester corresponding to each test subgroup in each test group in a set period are collected in the specific collection mode that:
Acquiring the body temperature of each tester corresponding to each test subgroup in each test group at each monitoring time point in a set period by using a human infrared thermometer to obtain the body temperature of each tester corresponding to each test subgroup in each test group at each monitoring time point in the set period, and taking the body temperature as a body temperature set of each tester corresponding to each test subgroup in each test group in the set period;
and collecting heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period through a heart rate monitoring instrument to obtain heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period, and taking the heart rates as heart rate sets of the testers corresponding to the test subgroups in the test groups in the set time period.
Preferably, the temperature state indexes of each test subgroup in each test group in the set period correspond to each tester, and the specific analysis mode is as follows:
Comparing the body temperature of each tester corresponding to each test subgroup in each test group in each monitoring time point in the set period with a reference body temperature interval stored in a database, if the body temperature of a certain monitoring time point is smaller than the lowest body temperature in the stored reference body temperature interval, marking the monitoring time point as a low-temperature time point, and if the body temperature of a certain monitoring time point is larger than the highest body temperature in the stored reference body temperature interval, marking the monitoring time point as a high-temperature time point, and counting to obtain each high-temperature time point and each low-temperature time point of each tester corresponding to each test subgroup in each test group in the set period;
Integrating adjacent high-temperature time points of each test subgroup corresponding to each tester in each test group in a set period to obtain each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period, counting and integrating duration of each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period to obtain duration of each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period, and recording as GT i jf, i as numbers of each test group, i=1, 2,..;
Similarly, analyzing to obtain the duration of the low-temperature time period of each tester corresponding to each test subgroup in each test group in the set time period, and marking as DT i jf;
The time length T of the set time period is obtained, the temperature state indexes WT i jf of the testers corresponding to the test subgroups in the test groups in the set time period are calculated according to the formula WT i jf=1/[(GTi jf/T)×a1+(DTi jf/T) x a2, and a1 and a2 are respectively expressed as weight factors corresponding to the set high-temperature time period duration and the set low-temperature time period duration, wherein a1+a2=1.
Preferably, the psychological index of each test subgroup in each test group in the set period corresponds to each tester, and the specific analysis mode is as follows:
Comparing the heart rate of each test subgroup corresponding to each tester in each test subgroup in each monitoring time point in the set time period with a reference heart rate interval stored in a database, if the heart rate of a certain monitoring time point is not in the stored reference heart rate interval, marking the monitoring time point as an abnormal time point, thereby obtaining each abnormal time point of each test subgroup corresponding to each tester in each test subgroup in the set time period, integrating adjacent each abnormal time point of each test subgroup corresponding to each tester in each test subgroup in the set time period, obtaining each abnormal time period of each test subgroup corresponding to each tester in each test subgroup in the set time period, further counting the duration of each abnormal time period of each test subgroup corresponding to each tester in each test subgroup in the set time period, and obtaining the abnormal heart rate duration of each test subgroup corresponding to each tester in each test subgroup in the set time period, and marking as XT i jf;
comparing and analyzing heart rates of the testers corresponding to the test subgroups in the test groups at each monitoring time point in the set time period to obtain heart rate variation indexes XB i jf of the testers corresponding to the test subgroups in the test groups in the set time period;
And calculating the heart state indexes TT i jf of each tester corresponding to each test subgroup in each test group within a set period according to a formula TT i jf=[1/(XTi jf/T)]×a5+(1/XBi jf) x a6, wherein a5 and a6 are respectively expressed as set heart rate abnormal time length and impact factors corresponding to heart rate change indexes, and a5+a6=1.
S5, analyzing state parameters: and acquiring the behavior state videos and the test feeling forms of the corresponding testers of the test subgroups in the test groups in the set time period in a set mode, and analyzing the behavior state videos and the test feeling forms to obtain the state parameters of the corresponding testers of the corresponding test subgroups in the test groups in the set time period.
Preferably, the state parameters of each test subgroup corresponding to each tester in each test group in the set period are specifically analyzed by the following steps:
Grabbing the morphological contours of the testers corresponding to the test subgroups in the test groups corresponding to the test time points in the behavior state videos of the testers in the set period, obtaining the morphological contours of the testers corresponding to the test subgroups in the test groups in the test time points, matching the morphological contours of the testers corresponding to the test subgroups in the test groups in the test time points with a morphological contour set corresponding to abnormal behaviors stored in a database, and if the morphological contours of a certain monitoring time point are successfully matched with the stored morphological contour set corresponding to the abnormal behaviors, marking the monitoring time point as an abnormal behavior time point, thereby obtaining the abnormal time points of the testers corresponding to the test subgroups in the test groups;
Integrating adjacent abnormal time points of the test subgroups corresponding to the testers in the test groups to obtain abnormal time periods of the test subgroups corresponding to the testers in the test groups, and acquiring the duration of the abnormal time periods of the test subgroups corresponding to the testers in the test groups as the duration of the abnormal behaviors of the test subgroups corresponding to the testers in the test groups, so as to count the abnormal behavior times of the test subgroups corresponding to the testers in the test groups;
extracting the difficulty scores of the parts of the testers corresponding to the test subgroups in the test groups in the set period from the test feeling forms of the testers corresponding to the test subgroups in the test groups in the set period, and matching the difficulty scores of the parts of the testers corresponding to the test subgroups in the test groups with the set influence factors corresponding to the parts to obtain the influence factors of the parts of the testers corresponding to the test subgroups in the test groups;
The abnormal behavior times, the abnormal behavior time length, the difficulty score of each part and the influence factors of each part of each test subgroup corresponding to each tester in each test subgroup constitute the state parameters of each tester corresponding to each test subgroup in a set period.
S6, drug exclusion analysis: and analyzing the state parameters of the corresponding testers of the test subgroups in the test groups in the set time period to obtain the drug repellency index of the corresponding testers of the test subgroups in the test groups in the set time period.
Preferably, the drug repellency index of each test subgroup in each test group corresponding to each tester in the set period of time is specifically analyzed as follows:
Extracting abnormal behavior times YN ijf of each test subgroup corresponding to each tester in each test group and time length YT ijf k of each abnormal behavior from state parameters of each tester corresponding to each tester in each test subgroup in a set period, wherein k is a number of each abnormal behavior, k is a positive integer, k=1, 2, z and z are the total number of abnormal behavior numbers;
Extracting the difficulty score PF ijf q of each part of each tester corresponding to each test subgroup in each test group and the influence factor BW ijf q of each part from the state parameters of each tester corresponding to each test subgroup in each test group in a set period, wherein q is represented as the number of each part, q=1, 2, w and q are positive integers, and w is represented as the total number of the part numbers;
According to the formula And calculating the drug repellency indexes YC i jf, b1, b2 and b3 of each test subgroup corresponding to each tester in each test group in the set period, wherein the drug repellency indexes are respectively expressed as the set weight factors corresponding to the abnormal behavior times, the abnormal behavior duration and the part difficulty score, and the weight factors are b1+b2+b3=1.
S7, analyzing the drug action: and analyzing the temperature state index, the heart state index and the drug repellency index of each tester corresponding to each test subgroup in each test group in the set period to obtain the drug action value of each tester corresponding to each test subgroup in each test group in the set period.
Preferably, the drug action values of each test subgroup in each test group correspond to each tester in the set period, and the specific analysis mode is as follows:
According to the formula YW i jf=WTi jf×c1+TTi jf×c2+(1/YCi jf) x c3, calculating the drug action value YW i jf of each tester corresponding to each test subgroup in each test group in a set period, wherein c1, c2 and c3 are respectively expressed as weight factors corresponding to the set temperature state index, the set heart state index and the set drug repellency index, and c1+c2+c3=1.
S8, analyzing the proper dosage of the medicine: and analyzing the proper dose of the biological medicine corresponding to each weight grade in each age group based on the medicine action value of each tester corresponding to each test subgroup in each test group in the set period, so as to obtain the proper dose of the biological medicine corresponding to each weight grade in each age group.
The invention has the beneficial effects that:
according to the invention, the test groups are divided into the test groups based on the ages of testers for preliminary screening, and meanwhile, the test groups are divided into the test subgroups based on the weights of the testers, so that the test doses of the test subgroups in the test groups are distributed based on the safety dose intervals corresponding to biological medicines, the defects of age groups and weight analysis tests of the testers in the prior art are overcome, and meanwhile, the proper dose tests of the testers under the safety condition are met, so that the comprehensiveness and scientificity of the biological medicine dose test are improved to a great extent, and the safety of the testers is further ensured.
According to the invention, the body temperature of each tester corresponding to each test subgroup in each test group is acquired, and the temperature state index of each tester corresponding to each test subgroup in each test group is obtained through analysis, so that the influence of the biological medicine test on the body temperature of the tester is fully considered, and the accuracy of the result of the biological medicine test is improved to a great extent.
According to the invention, the heart rate of each tester corresponding to each test subgroup in each test group is collected, and the heart state index of each tester corresponding to each test subgroup in each test group is obtained through analysis, so that reliable data support is provided for drug action analysis in subsequent biological medicine tests, and the influence of the biological medicine test on the heart rate of the tester can be intuitively reflected.
According to the invention, the behavior state videos and the test feeling forms of the testers corresponding to the test subgroups in the test groups are collected, the state parameters of the testers corresponding to the test subgroups in the test groups are obtained based on the analysis, and then the drug repellency indexes of the testers corresponding to the test subgroups in the test groups are analyzed based on the state parameters of the testers corresponding to the test subgroups in the test groups, so that adverse reactions to the testers in the biological medicine test are intuitively known, the self feeling of the testers in the biological medicine test can be comprehensively collected, and the accuracy and the reliability of the drug repellency index analysis results of the testers corresponding to the test subgroups in the test groups are greatly improved.
According to the invention, based on the temperature state index, the heart state index and the drug repellency index analysis of each tester corresponding to each test subgroup in the test group, the drug action values of each tester corresponding to each test subgroup in each test group are obtained, and further the drug action values of each tester corresponding to each test subgroup in each test group are subjected to mutual comparison analysis, so that the proper dosage of each weight grade in each age group corresponding to the biological medicine is obtained, the influence of each aspect on the drug action values is comprehensively considered, and meanwhile, the proper dosage of each weight grade in each age group is obtained through comparison screening analysis, so that the influence of individual difference on the drug action values is avoided to a great extent, and the problem that the low dosage of the biological medicine is invalid or the high dosage of the biological medicine is harmful to human bodies is eliminated.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of the method steps of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention is an optimized matching method for biomedical clinical test, comprising: the method comprises the following steps:
S1, test group allocation: the method comprises the steps of obtaining ages of testers in a set age range, matching the ages of the testers with age thresholds corresponding to the set age ranges to obtain age ranges corresponding to the testers, classifying and sorting the testers according to the same age ranges to obtain the testers in the age ranges, and taking the testers as test groups.
It should be noted that the set age range is specifically 20 to 45 years old, the age threshold corresponding to the age range is specifically 20 to 24 years old, the age threshold corresponding to the second age range is 25 to 29 years old, and so on.
S2, the test sub-components are distributed: the method comprises the steps of obtaining the weight of each tester in each test group, dividing each test group into test subgroups based on the weight of each tester in each test group, and obtaining each test subgroup corresponding to each test group, wherein the specific dividing mode is as follows: and matching the weight of each tester in each test group with the weight section corresponding to the set weight grade to obtain the weight grade of each tester in each test group, and dividing the testers with different weight grades according to the number of testers in the set reference test subgroup to obtain each tester in each test subgroup.
In a specific embodiment, the number of testers in the set reference test subgroup is three times the number of weight classes, for example, the number of weight classes is five, the number of testers in the set reference test subgroup is fifteen, and three testers are respectively extracted from the five testers in the weight class as one test subgroup.
S3, dose test analysis: and acquiring a safety dose interval corresponding to the biological medicine, setting a plurality of test doses based on the safety dose interval corresponding to the biological medicine to obtain each test dose corresponding to the biological medicine, and performing a dose test on each test subgroup corresponding to each test subgroup according to each test dose corresponding to the biological medicine to obtain the test dose corresponding to each test subgroup in each test subgroup.
It should be noted that the number of the test doses is equal to the number of the test subgroups, so that the test doses corresponding to the biological medicine can be comprehensively tested, the test dose difference of each test subgroup is ensured, and the comprehensiveness and scientificity of the biological medicine dose test are further improved.
According to the invention, the test groups are divided into the test groups based on the ages of testers for preliminary screening, and meanwhile, the test groups are divided into the test subgroups based on the weights of the testers, so that the test doses of the test subgroups in the test groups are distributed based on the safety dose intervals corresponding to biological medicines, the defects of age groups and weight analysis tests of the testers in the prior art are overcome, and meanwhile, the proper dose tests of the testers under the safety condition are met, so that the comprehensiveness and scientificity of the biological medicine dose test are improved to a great extent, and the safety of the testers is further ensured.
S4, basic data analysis: the body temperature set and the heart rate set of each tester corresponding to each test subgroup in each test group in a set period are collected, and the specific collection mode is as follows: acquiring the body temperature of each tester corresponding to each test subgroup in each test group at each monitoring time point in a set period by using a human infrared thermometer to obtain the body temperature of each tester corresponding to each test subgroup in each test group at each monitoring time point in the set period, and taking the body temperature as a body temperature set of each tester corresponding to each test subgroup in each test group in the set period;
and collecting heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period through a heart rate monitoring instrument to obtain heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period, and taking the heart rates as heart rate sets of the testers corresponding to the test subgroups in the test groups in the set time period.
Based on the body temperature set analysis of each tester corresponding to each test subgroup in each test group in the set period, the temperature state index of each tester corresponding to each test subgroup in each test group in the set period is obtained, and the specific analysis mode is as follows:
Comparing the body temperature of each tester corresponding to each test subgroup in each test group in each monitoring time point in the set period with a reference body temperature interval stored in a database, if the body temperature of a certain monitoring time point is smaller than the lowest body temperature in the stored reference body temperature interval, marking the monitoring time point as a low-temperature time point, and if the body temperature of a certain monitoring time point is larger than the highest body temperature in the stored reference body temperature interval, marking the monitoring time point as a high-temperature time point, and counting to obtain each high-temperature time point and each low-temperature time point of each tester corresponding to each test subgroup in each test group in the set period;
Integrating adjacent high-temperature time points of each test subgroup corresponding to each tester in each test group in a set period to obtain each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period, counting and integrating duration of each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period to obtain duration of each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period, and recording as GT i jf, i as numbers of each test group, i=1, 2,..;
Integrating adjacent low-temperature time points of the test subgroups of the test groups corresponding to the testers in the set period to obtain low-temperature time periods of the test subgroups of the test groups corresponding to the testers in the set period, counting duration time of the low-temperature time periods of the test subgroups of the test groups corresponding to the testers in the set period, integrating the duration time of the low-temperature time periods of the test subgroups of the test groups corresponding to the testers in the set period, and recording the duration time as DT i jf.
The time length T of the set time period is obtained, the temperature state indexes WT i jf of the testers corresponding to the test subgroups in the test groups in the set time period are calculated according to the formula WT i jf=1/[(GTi jf/T)×a1+(DTi jf/T) x a2, and a1 and a2 are respectively expressed as weight factors corresponding to the set high-temperature time period duration and the set low-temperature time period duration, wherein a1+a2=1.
According to the invention, the body temperature of each tester corresponding to each test subgroup in each test group is acquired, and the temperature state index of each tester corresponding to each test subgroup in each test group is obtained through analysis, so that the influence of the biological medicine test on the body temperature of the tester is fully considered, and the accuracy of the result of the biological medicine test is improved to a great extent.
Based on heart rate set analysis of each test subgroup corresponding to each tester in each test subgroup in the set period, the heart state index of each test subgroup corresponding to each tester in each test subgroup in the set period is obtained, and the specific analysis mode is as follows:
Comparing the heart rate of each test subgroup corresponding to each tester in each test subgroup in each monitoring time point in the set time period with a reference heart rate interval stored in a database, if the heart rate of a certain monitoring time point is not in the stored reference heart rate interval, marking the monitoring time point as an abnormal time point, thereby obtaining each abnormal time point of each test subgroup corresponding to each tester in each test subgroup in the set time period, integrating adjacent each abnormal time point of each test subgroup corresponding to each tester in each test subgroup in the set time period, obtaining each abnormal time period of each test subgroup corresponding to each tester in each test subgroup in the set time period, further counting the duration of each abnormal time period of each test subgroup corresponding to each tester in each test subgroup in the set time period, and obtaining the abnormal heart rate duration of each test subgroup corresponding to each tester in each test subgroup in the set time period, and marking as XT i jf;
And (3) screening heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period from heart rates of the testers corresponding to the test subgroups in the test groups at the initial monitoring time points, wherein the heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period are marked as XL ijf 0, the heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period are marked as XL ijf p, p is represented as the number of the monitoring time points, p=1, 2, t and p are positive integers, and t is represented as the total number of the monitoring time point numbers.
According to the formulaCalculating heart rate change indexes XB i jf,/>, corresponding to the testers, of each test subgroup in each test group in a set periodEach test subgroup in each test group, expressed as the p-1 th monitoring time point within the set period, corresponds to each subject's heart rate, and a3, a4 are expressed as set weighting factors, a3+a4=1.
And calculating the heart state indexes TT i jf of each tester corresponding to each test subgroup in each test group within a set period according to a formula TT i jf=[1/(XTi jf/T)]×a5+(1/XBi jf) x a6, wherein a5 and a6 are respectively expressed as set heart rate abnormal time length and impact factors corresponding to heart rate change indexes, and a5+a6=1.
According to the invention, the heart rate of each tester corresponding to each test subgroup in each test group is collected, and the heart state index of each tester corresponding to each test subgroup in each test group is obtained through analysis, so that reliable data support is provided for drug action analysis in subsequent biological medicine tests, and the influence of the biological medicine test on the heart rate of the tester can be intuitively reflected.
S5, analyzing state parameters: acquiring the behavior state videos and the test feeling forms of the corresponding testers of each test subgroup in each test group in a set period by a set mode, wherein the specific acquisition mode is as follows:
The behavior state videos of the corresponding testers of each test subgroup in each test group in a set period are collected, and the specific collection mode is as follows: and acquiring behavior state videos of the testers corresponding to the test subgroups in the test groups in the set time period through the camera to obtain behavior state videos of the testers corresponding to the test subgroups in the test groups in the set time period. It should be noted that, according to relevant laws and regulations, in order to protect personal privacy, the applicant may need to obtain and process personal information of a tester in the present patent application. Here, the applicant is a serious promise, will strictly adhere to relevant laws and regulations, be responsible for personal information confidentiality of the experimenter, and will not use the personal information of the experimenter for other purposes. Meanwhile, the applicant will also take necessary technical and organizational measures to ensure the safety and confidentiality of personal information of the testers. The experimenter, while agreeing to provide personal information, also understands and agrees to the above-described authorizations and commitments.
Further, the test experience evaluation of each test subgroup corresponding to each tester in each test group in the set period is collected, specifically: filling in a form for the test feelings of each test subgroup corresponding to each tester in each test group in a set period, wherein the contents of the form are specifically as follows: "discomfort score for each site", for example: head difficulty score, waist difficulty score, leg difficulty score, and the like. Note that the difficulty score is at most ten times.
The state parameters of each test subgroup corresponding to each tester in each test group in the set period are as follows: grabbing the morphological contours of the testers corresponding to the test subgroups in the test groups corresponding to the test time points in the behavior state videos of the testers in the set period, obtaining the morphological contours of the testers corresponding to the test subgroups in the test groups in the test time points, matching the morphological contours of the testers corresponding to the test subgroups in the test groups in the test time points with a morphological contour set corresponding to abnormal behaviors stored in a database, and if the morphological contours of a certain monitoring time point are successfully matched with the stored morphological contour set corresponding to the abnormal behaviors, marking the monitoring time point as an abnormal behavior time point, thereby obtaining the abnormal time points of the testers corresponding to the test subgroups in the test groups;
in a specific embodiment, the abnormal behavior includes: vomiting, retching, tremble, etc.
Integrating adjacent abnormal time points of the test subgroups corresponding to the testers in the test groups to obtain abnormal time periods of the test subgroups corresponding to the testers in the test groups, and acquiring the duration of the abnormal time periods of the test subgroups corresponding to the testers in the test groups as the duration of the abnormal behaviors of the test subgroups corresponding to the testers in the test groups, so as to count the abnormal behavior times of the test subgroups corresponding to the testers in the test groups;
extracting the difficulty scores of the parts of the testers corresponding to the test subgroups in the test groups in the set period from the test feeling forms of the testers corresponding to the test subgroups in the test groups in the set period, and matching the difficulty scores of the parts of the testers corresponding to the test subgroups in the test groups with the set influence factors corresponding to the parts to obtain the influence factors of the parts of the testers corresponding to the test subgroups in the test groups;
The abnormal behavior times, the abnormal behavior time length, the difficulty score of each part and the influence factors of each part of each test subgroup corresponding to each tester in each test subgroup constitute the state parameters of each tester corresponding to each test subgroup in a set period.
S6, drug exclusion analysis: based on the state parameter analysis of each test subgroup corresponding to each tester in each test subgroup in the set period, the drug repellency index of each test subgroup corresponding to each tester in each test subgroup in the set period is obtained, and the specific analysis steps are as follows:
Extracting abnormal behavior times YN ijf of each test subgroup corresponding to each tester in each test group and time length YT ijf k of each abnormal behavior from state parameters of each tester corresponding to each tester in each test subgroup in a set period, wherein k is a number of each abnormal behavior, k is a positive integer, k=1, 2, z and z are the total number of abnormal behavior numbers;
Extracting the difficulty score PF ijf q of each part of each tester corresponding to each test subgroup in each test group and the influence factor BW ijf q of each part from the state parameters of each tester corresponding to each test subgroup in each test group in a set period, wherein q is represented as the number of each part, q=1, 2, w and q are positive integers, and w is represented as the total number of the part numbers;
According to the formula And calculating the drug repellency indexes YC i jf, b1, b2 and b3 of each test subgroup corresponding to each tester in each test group in the set period, wherein the drug repellency indexes are respectively expressed as the set weight factors corresponding to the abnormal behavior times, the abnormal behavior duration and the part difficulty score, and the weight factors are b1+b2+b3=1.
The number of abnormal behaviors of each tester and the score of the difficulty of each part corresponding to each test subgroup in each test group are normalized and the values are taken to be substituted into a formula for calculation.
According to the invention, the behavior state videos and the test feeling forms of the testers corresponding to the test subgroups in the test groups are collected, the state parameters of the testers corresponding to the test subgroups in the test groups are obtained based on the analysis, and then the drug repellency indexes of the testers corresponding to the test subgroups in the test groups are analyzed based on the state parameters of the testers corresponding to the test subgroups in the test groups, so that adverse reactions to the testers in the biological medicine test are intuitively known, the self feeling of the testers in the biological medicine test can be comprehensively collected, and the accuracy and the reliability of the drug repellency index analysis results of the testers corresponding to the test subgroups in the test groups are greatly improved.
S7, analyzing the drug action: based on the temperature state index, the heart state index and the drug repellency index of each tester corresponding to each test subgroup in each test group in the set period, the drug action value of each tester corresponding to each test subgroup in each test group in the set period is obtained by analysis, specifically:
According to the formula YW i jf=WTi jf×c1+TTi jf×c2+(1/YCi jf) x c3, calculating the drug action value YW i jf of each tester corresponding to each test subgroup in each test group in a set period, wherein c1, c2 and c3 are respectively expressed as weight factors corresponding to the set temperature state index, the set heart state index and the set drug repellency index, and c1+c2+c3=1.
S8, analyzing the proper dosage of the medicine: based on the drug action values of the test sub-groups corresponding to the test persons in the test groups in the set time period, analyzing the proper dosages of the biological medicine corresponding to the weight grades in the age groups to obtain the proper dosages of the biological medicine corresponding to the weight grades in the age groups, wherein the specific analysis mode is as follows:
Acquiring the test dose of each tester corresponding to each test subgroup in each test group in a set period based on the test dose corresponding to each test subgroup in each test group;
Extracting the weight grade of each tester corresponding to each tester in each test group in a set period, classifying the testers corresponding to the same weight grade in each test group to obtain each tester corresponding to each weight grade in each test group, extracting the drug action value of each tester corresponding to each weight grade in each test group from the drug action value of each tester corresponding to each tester in each test group in the set period, and simultaneously acquiring the test dosage of each tester corresponding to each weight grade in each test group based on the test dosage of each tester corresponding to each tester in each test group in the set period;
Arranging the drug action values of the testers corresponding to the weight grades of each test group in sequence from large to small, and extracting testers corresponding to the first three drug action values from the drug action values, namely a first tester, a second tester and a third tester, so as to obtain the first tester, the second tester and the third tester corresponding to the weight grades of each test group, and further obtaining the test doses corresponding to the first tester, the second tester and the third tester corresponding to the weight grades of each test group based on the test doses of the testers corresponding to the weight grades of each test group;
And carrying out average treatment on the test doses corresponding to the first tester, the second tester and the third tester of each weight grade of each test group to obtain average doses corresponding to the first tester, the second tester and the third tester of each weight grade of each test group, recording the average doses as proper doses, and obtaining proper doses corresponding to each weight grade of each test group as proper doses corresponding to each weight grade of each age group of biological medicine.
According to the invention, based on the temperature state index, the heart state index and the drug repellency index analysis of each tester corresponding to each test subgroup in the test group, the drug action values of each tester corresponding to each test subgroup in each test group are obtained, and further the drug action values of each tester corresponding to each test subgroup in each test group are subjected to mutual comparison analysis, so that the proper dosage of each weight grade in each age group corresponding to the biological medicine is obtained, the influence of each aspect on the drug action values is comprehensively considered, and meanwhile, the proper dosage of each weight grade in each age group is obtained through comparison screening analysis, so that the influence of individual difference on the drug action values is avoided to a great extent, and the problem that the low dosage of the biological medicine is invalid or the high dosage of the biological medicine is harmful to human bodies is eliminated.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art of describing particular embodiments without departing from the structures of the invention or exceeding the scope of the invention as defined in the accompanying drawings are intended to be included within the scope of the invention.
Claims (4)
1. The optimized matching method for the biomedical clinical test is characterized by comprising the following steps of:
S1, test group allocation: obtaining the ages of all testers in the set age range, matching the ages of the testers with age thresholds corresponding to all the set age ranges to obtain age ranges corresponding to all the testers, classifying and sorting all the testers according to the same age ranges to obtain all the testers in all the age ranges, and taking the testers as all the test groups;
S2, the test sub-components are distributed: acquiring the weight of each tester in each test group, dividing each test group into test subgroups based on the weight of each tester in each test group, and obtaining each test subgroup corresponding to each test group;
S3, dose test analysis: acquiring a safety dose interval corresponding to the biological medicine, setting a plurality of test doses based on the safety dose interval corresponding to the biological medicine to obtain each test dose corresponding to the biological medicine, and carrying out a dose test on each test subgroup corresponding to each test subgroup according to each test dose corresponding to the biological medicine to obtain each test dose corresponding to each test subgroup in each test subgroup;
s4, basic data analysis: collecting body temperature sets and heart rate sets of testers corresponding to all test subgroups in all test groups in a set period, analyzing the body temperature sets of the testers corresponding to all test subgroups in all test groups in the set period to obtain the temperature state indexes of the testers corresponding to all test subgroups in all test groups in the set period, and analyzing the heart rate sets of the testers corresponding to all test subgroups in all test groups in the set period to obtain the heart state indexes of the testers corresponding to all test subgroups in all test groups in the set period;
Comparing the body temperature of each tester corresponding to each test subgroup in each test group in each monitoring time point in the set period with a reference body temperature interval stored in a database, if the body temperature of a certain monitoring time point is smaller than the lowest body temperature in the stored reference body temperature interval, marking the monitoring time point as a low-temperature time point, and if the body temperature of a certain monitoring time point is larger than the highest body temperature in the stored reference body temperature interval, marking the monitoring time point as a high-temperature time point, and counting to obtain each high-temperature time point and each low-temperature time point of each tester corresponding to each test subgroup in each test group in the set period;
Integrating adjacent high-temperature time points of each test subgroup corresponding to each tester in each test group in a set period to obtain each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period, counting and integrating duration of each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period to obtain duration of each high-temperature period of each test subgroup corresponding to each tester in each test group in the set period, and recording as GT i jf, i as numbers of each test group, i=1, 2,..;
Similarly, analyzing to obtain the duration of the low-temperature time period of each tester corresponding to each test subgroup in each test group in the set time period, and marking as DT i jf;
Acquiring the duration T of a set period, and calculating the temperature state indexes WT i jf of each tester corresponding to each test subgroup in each test group in the set period according to a formula WT i jf=1/[(GTi jf/T)×a1+(DTi jf/T) x a2, wherein a1 and a2 are respectively expressed as weight factors corresponding to the duration of the set high-temperature period and the duration of the set low-temperature period, and a1+a2=1;
Comparing the heart rate of each test subgroup corresponding to each tester in each test subgroup in each monitoring time point in the set time period with a reference heart rate interval stored in a database, if the heart rate of a certain monitoring time point is not in the stored reference heart rate interval, marking the monitoring time point as an abnormal time point, thereby obtaining each abnormal time point of each test subgroup corresponding to each tester in each test subgroup in the set time period, integrating adjacent each abnormal time point of each test subgroup corresponding to each tester in each test subgroup in the set time period, obtaining each abnormal time period of each test subgroup corresponding to each tester in each test subgroup in the set time period, further counting the duration of each abnormal time period of each test subgroup corresponding to each tester in each test subgroup in the set time period, and obtaining the abnormal heart rate duration of each test subgroup corresponding to each tester in each test subgroup in the set time period, and marking as XT i jf;
comparing and analyzing heart rates of the testers corresponding to the test subgroups in the test groups at each monitoring time point in the set time period to obtain heart rate variation indexes XB i jf of the testers corresponding to the test subgroups in the test groups in the set time period;
according to a formula TT i jf=[1/(XTi jf/T)]×a5+(1/XBi jf) x a6, calculating the heart state indexes TT i jf of each tester corresponding to each test subgroup in each test group in a set period, wherein a5 and a6 are respectively expressed as set heart rate abnormal time length and impact factors corresponding to heart rate change indexes, and a5+a6=1;
S5, analyzing state parameters: acquiring behavior state videos and test feeling forms of corresponding testers of all test subgroups in all test groups in a set period through a set mode, and analyzing based on the videos to obtain state parameters of corresponding testers of all test subgroups in all test groups in the set period;
S6, drug exclusion analysis: obtaining the drug repellency index of each tester corresponding to each test subgroup in the set period based on the state parameter analysis of each tester corresponding to each test subgroup in the set period; extracting abnormal behavior times YN ijf of each test subgroup corresponding to each tester in each test group and time length YT ijf k of each abnormal behavior from state parameters of each tester corresponding to each tester in each test subgroup in a set period, wherein k is a number of each abnormal behavior, k is a positive integer, k=1, 2, z and z are the total number of abnormal behavior numbers;
Extracting the difficulty score PF ijf q of each part of each tester corresponding to each test subgroup in each test group and the influence factor BW ijf q of each part from the state parameters of each tester corresponding to each test subgroup in each test group in a set period, wherein q is represented as the number of each part, q=1, 2, w and q are positive integers, and w is represented as the total number of the part numbers;
According to the formula Calculating the drug repellency indexes YC i jf, b1, b2 and b3 of each test subgroup corresponding to each tester in each test group in a set period, wherein the drug repellency indexes are respectively expressed as weight factors corresponding to the set abnormal behavior times, abnormal behavior duration and part difficulty scores, and the weight factors are b1+b2+b3=1;
S7, analyzing the drug action: analyzing the temperature state index, the heart state index and the drug repellency index of each tester corresponding to each test subgroup in each test group in a set period to obtain the drug action value of each tester corresponding to each test subgroup in each test group in the set period; calculating the drug action value YW i jf of each tester corresponding to each test subgroup in each test group in a set period according to a formula YW i jf=WTi jf×c1+TTi jf×c2+(1/YCi jf) x c3, wherein c1, c2 and c3 are respectively expressed as weight factors corresponding to the set temperature state index, the heart state index and the drug repulsion index, and c1+c2+c3=1;
s8, analyzing the proper dosage of the medicine: and analyzing the proper dose of the biological medicine corresponding to each weight grade in each age group based on the medicine action value of each tester corresponding to each test subgroup in each test group in the set period, so as to obtain the proper dose of the biological medicine corresponding to each weight grade in each age group.
2. The optimized matching method for biomedical clinical trial according to claim 1, wherein the dividing of each trial group into each trial subgroup based on the body weight of each trial participant in each trial group is as follows:
And matching the weight of each tester in each test group with the weight section corresponding to the set weight grade to obtain the weight grade of each tester in each test group, and dividing the testers with different weight grades according to the number of testers in the set reference test subgroup to obtain each tester in each test subgroup.
3. The optimized matching method for biomedical clinical trials according to claim 1, wherein the collecting the body temperature set and the heart rate set of each test subgroup in each test group in a set period of time is as follows:
Acquiring the body temperature of each tester corresponding to each test subgroup in each test group at each monitoring time point in a set period by using a human infrared thermometer to obtain the body temperature of each tester corresponding to each test subgroup in each test group at each monitoring time point in the set period, and taking the body temperature as a body temperature set of each tester corresponding to each test subgroup in each test group in the set period;
and collecting heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period through a heart rate monitoring instrument to obtain heart rates of the testers corresponding to the test subgroups in the test groups at the monitoring time points in the set time period, and taking the heart rates as heart rate sets of the testers corresponding to the test subgroups in the test groups in the set time period.
4. The optimized matching method for biomedical clinical trial according to claim 1, wherein the state parameters of each test subgroup in each test group correspond to each tester in the set period of time, and the specific analysis steps are as follows:
Grabbing the morphological contours of the testers corresponding to the test subgroups in the test groups corresponding to the test time points in the behavior state videos of the testers in the set period, obtaining the morphological contours of the testers corresponding to the test subgroups in the test groups in the test time points, matching the morphological contours of the testers corresponding to the test subgroups in the test groups in the test time points with a morphological contour set corresponding to abnormal behaviors stored in a database, and if the morphological contours of a certain monitoring time point are successfully matched with the stored morphological contour set corresponding to the abnormal behaviors, marking the monitoring time point as an abnormal behavior time point, thereby obtaining the abnormal time points of the testers corresponding to the test subgroups in the test groups;
Integrating adjacent abnormal time points of the test subgroups corresponding to the testers in the test groups to obtain abnormal time periods of the test subgroups corresponding to the testers in the test groups, and acquiring the duration of the abnormal time periods of the test subgroups corresponding to the testers in the test groups as the duration of the abnormal behaviors of the test subgroups corresponding to the testers in the test groups, so as to count the abnormal behavior times of the test subgroups corresponding to the testers in the test groups;
extracting the difficulty scores of the parts of the testers corresponding to the test subgroups in the test groups in the set period from the test feeling forms of the testers corresponding to the test subgroups in the test groups in the set period, and matching the difficulty scores of the parts of the testers corresponding to the test subgroups in the test groups with the set influence factors corresponding to the parts to obtain the influence factors of the parts of the testers corresponding to the test subgroups in the test groups;
The abnormal behavior times, the abnormal behavior time length, the difficulty score of each part and the influence factors of each part of each test subgroup corresponding to each tester in each test subgroup constitute the state parameters of each tester corresponding to each test subgroup in a set period.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410115717.4A CN117649909B (en) | 2024-01-29 | 2024-01-29 | Optimized matching method for biomedical clinical test |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410115717.4A CN117649909B (en) | 2024-01-29 | 2024-01-29 | Optimized matching method for biomedical clinical test |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117649909A CN117649909A (en) | 2024-03-05 |
| CN117649909B true CN117649909B (en) | 2024-04-19 |
Family
ID=90046233
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410115717.4A Active CN117649909B (en) | 2024-01-29 | 2024-01-29 | Optimized matching method for biomedical clinical test |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117649909B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109493942A (en) * | 2019-01-16 | 2019-03-19 | 中国人民解放军66399部队 | A kind of drug abortion method for canine |
| CN113971997A (en) * | 2021-10-12 | 2022-01-25 | 浙江太美医疗科技股份有限公司 | Method and system for determining drug delivery amount in clinical trial |
| CN116825276A (en) * | 2023-07-10 | 2023-09-29 | 辽宁千一测试评价科技发展有限公司 | Intelligent drug authentication test drug feeding method and device |
| CN116913548A (en) * | 2023-06-09 | 2023-10-20 | 魔方医药科技(苏州)有限公司 | Adverse reaction data analysis method, device, electronic equipment and storage medium |
| CN117133478A (en) * | 2023-10-08 | 2023-11-28 | 北京舒曼德医药科技开发有限公司 | Intelligent presentation system of drug response data based on clinical test data |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200095307A1 (en) * | 2018-09-21 | 2020-03-26 | Alexion Pharmaceuticals, Inc. | Compositions and methods for the treatment of neuromyelitis optica |
-
2024
- 2024-01-29 CN CN202410115717.4A patent/CN117649909B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109493942A (en) * | 2019-01-16 | 2019-03-19 | 中国人民解放军66399部队 | A kind of drug abortion method for canine |
| CN113971997A (en) * | 2021-10-12 | 2022-01-25 | 浙江太美医疗科技股份有限公司 | Method and system for determining drug delivery amount in clinical trial |
| CN116913548A (en) * | 2023-06-09 | 2023-10-20 | 魔方医药科技(苏州)有限公司 | Adverse reaction data analysis method, device, electronic equipment and storage medium |
| CN116825276A (en) * | 2023-07-10 | 2023-09-29 | 辽宁千一测试评价科技发展有限公司 | Intelligent drug authentication test drug feeding method and device |
| CN117133478A (en) * | 2023-10-08 | 2023-11-28 | 北京舒曼德医药科技开发有限公司 | Intelligent presentation system of drug response data based on clinical test data |
Non-Patent Citations (3)
| Title |
|---|
| "Comparison of cardioprotective ef!cacy resulting from a combination of atorvastatin and ischaemic post-conditioning in diabetic and non-diabetic rats";Ying Fan等;《Clinical and Experimental Pharmacology and Physiology》;20121231;全文 * |
| "不同剂量蒲地蓝消炎口服液治疗细菌感染 所致成人急性咽炎/扁桃体炎的 多中心临床研究";李丁蕾等;《中国实验方剂学杂志》;20231031;第29卷(第19期);全文 * |
| "小剂量泵注右美托咪定在膝关节全麻手术 患者的临床研究";曾晓慧;《中国临床药理学杂志》;20231130;第39卷(第21期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117649909A (en) | 2024-03-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Patel et al. | A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology | |
| Ben-Shakhar et al. | Psychophysiological detection through the guilty knowledge technique: effects of mental countermeasures. | |
| FI102872B (en) | Observation of anesthesia depth | |
| Surangsrirat et al. | Support vector machine classification of Parkinson's disease and essential tremor subjects based on temporal fluctuation | |
| CN107945094B (en) | Digital rehabilitation system for drug-dropping personnel | |
| CN109106350A (en) | The preliminary screening method of the Sleep Apnea-hypopnea Syndrome of low physiological stress | |
| van Brakel et al. | Intl-a-and Inter-Tester Reliability of Sensibility Testing in Leprosy' | |
| Granat et al. | Quantifying the cadence of free-living walking using event-based analysis | |
| Weinberg | The effects of success and failure on the patterning of neuromuscular energy | |
| Krebs | Measurement theory | |
| Stuart et al. | Analysis of free-living mobility in people with mild traumatic brain injury and healthy controls: quality over quantity | |
| CN109715049A (en) | For the multi-modal physiological stimulation of traumatic brain injury and the agreement and signature of assessment | |
| Solomon et al. | Assessment of orofacial strength in patients with dysarthria | |
| CN106901689A (en) | Cognitive and motor function detecting system and data processing method based on interaction in kind | |
| CN117649909B (en) | Optimized matching method for biomedical clinical test | |
| Chester et al. | An extended index to quantify normality of gait in children | |
| Bronstein et al. | Can clinicians accurately predict which patients are misusing their medications? | |
| CN110537911A (en) | Latent energy talent evaluation method and system | |
| Forseth et al. | A comparison of accelerometer cut-points for measuring physical activity and sedentary time in adolescents with Down syndrome | |
| Gong et al. | Correlations between inertial body sensor measures and clinical measures in multiple sclerosis | |
| CN112493995A (en) | Anesthesia state evaluation system and method suitable for patients of different ages | |
| Bowling et al. | Discriminant analysis of electroencephalograms recorded from renal patients | |
| Becker et al. | The psychophysiological assessment of juvenile | |
| Hill et al. | Constructs underlying measures of sensory-motor functions | |
| CN110192880A (en) | Based on the lie detecting method for more leading EEG signals Granger Causality |
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 |