CN109215784B - Method for analyzing physiological parameter values - Google Patents
Method for analyzing physiological parameter values Download PDFInfo
- Publication number
- CN109215784B CN109215784B CN201710522331.5A CN201710522331A CN109215784B CN 109215784 B CN109215784 B CN 109215784B CN 201710522331 A CN201710522331 A CN 201710522331A CN 109215784 B CN109215784 B CN 109215784B
- Authority
- CN
- China
- Prior art keywords
- physiological parameter
- value
- pattern
- parameter value
- analyzing
- 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
Images
Abstract
A method of analyzing a value of a physiological parameter, comprising: calculating the quantity proportion of the physiological parameter values which are too high, the quantity proportion of the physiological parameter values which are normal and the quantity proportion of the physiological parameter values which are too low according to the plurality of physiological parameter values corresponding to the event labels; and generating a first indicator corresponding to the event label according to the quantity proportion, wherein the first indicator represents the quantity proportion of the physiological parameter value which is too high, the quantity proportion of the physiological parameter value which is normal and the quantity proportion of the physiological parameter value which is too low in a first mode, a second mode and a third mode respectively, and the size proportion of the first mode, the second mode and the third mode in the first indicator is respectively the same as the quantity proportion of the physiological parameter value which is too high, the quantity proportion of the physiological parameter value which is normal and the quantity proportion of the physiological parameter value which is too low. The distribution and the change of the blood sugar value of the corresponding event can be easily observed and tracked by the user, so that the medication judgment of the user is further assisted.
Description
Technical Field
The present invention relates to a method for analyzing physiological parameter values, and more particularly, to a method for analyzing physiological parameter values in combination with data visualization.
Background
Chronic patients are usually characterized by unstable physiological parameters, and it is often necessary to monitor whether the physiological parameters are normal or not regularly, so as to avoid the failure of proper immediate treatment during the onset of disease. For example, diabetics need to measure their blood glucose levels frequently to monitor whether the blood glucose levels are normal.
One of the existing ways to analyze the value of a physiological parameter is to display the recorded physiological parameter data in an electronic device. For example, the blood sugar level before and after a meal is displayed every day, and a warning is displayed when the blood sugar level is too high or too low; however, the distribution of the blood glucose level before or after a meal is not easily seen at a glance by the user only through the display of the data, and therefore, the tracking of the blood glucose level is also not easily performed.
In addition, the proportion of normal samples to abnormal samples in a plurality of physiological parameter values is presented by using a pie chart; however, the pie chart does not distinguish the event or time period during which the physiological parameter occurred, so the user cannot determine the event or time period corresponding to the abnormal physiological parameter value from the pie chart, and thus the help of the user is limited.
Disclosure of Invention
The objective of the present invention is to provide a method for analyzing physiological parameter values based on event and data visualization.
The method for analyzing physiological parameter values of the present invention is implemented by an electronic device, which stores a plurality of physiological parameter values corresponding to an event tag. The method for analyzing the physiological parameter value comprises a step (a) and a step (b).
The step (a) is to calculate the quantitative proportion of the physiological parameter value which is too high, the quantitative proportion of the physiological parameter value which is normal and the quantitative proportion of the physiological parameter value which is too low.
The step (b) is to generate a first indicator corresponding to the event label according to the quantity ratio, wherein the first indicator represents the ratio of the quantity of the physiological parameter value that is too high, the ratio of the quantity of the physiological parameter value that is normal and the ratio of the quantity of the physiological parameter value that is too low in a first pattern, a second pattern and a third pattern, respectively, and the size ratios of the first pattern, the second pattern and the third pattern in the first indicator are respectively the same as the ratio of the quantity of the physiological parameter value that is too high, the ratio of the quantity of the physiological parameter value that is normal and the ratio of the quantity of the physiological parameter value that is too low.
In the step (b), when the quantitative proportion of the physiological parameter value that is too high, the quantitative proportion of the physiological parameter value that is normal, and the quantitative proportion of the physiological parameter value that is too low are all greater than zero, the first pattern is adjacent to the second pattern, the second pattern is adjacent to the third pattern, and the first pattern is not adjacent to the third pattern.
The method for analyzing the physiological parameter value is the blood sugar value, and the event label is one of midnight, morning start, before breakfast, after breakfast, before lunch, after lunch, before dinner, after dinner, before sleeping, fasting, before exercise, after exercise, before medicine application and after medicine application.
The method for analyzing physiological parameter values of the present invention further comprises a step (c): generating a second indicator corresponding to the event label based on the value of the physiological parameter, the size of the second indicator positively correlating to the average value of the physiological parameter.
The method for analyzing physiological parameter values of the present invention, each physiological parameter value corresponding to one of a plurality of event tags, further comprises a step (d): and generating a trend graph corresponding to the event labels according to the physiological parameter values, wherein the trend graph displays the physiological parameter values corresponding to different event labels.
In the method for analyzing physiological parameter values of the present invention, in the step (d), the trend graph includes a simple moving average line corresponding to the event label.
In the method for analyzing physiological parameter values of the present invention, in the step (d), for each event label, the trend graph represents the newest of all physiological parameter values corresponding to the event label in a first pattern, and represents a non-newest physiological parameter value corresponding to the event label in a second pattern.
In the step (a), the event label corresponds to a first threshold value and a second threshold value smaller than the first threshold value, and for each physiological parameter value, when the physiological parameter value is larger than the first threshold value, the physiological parameter value is determined to be too high; when the physiological parameter value is smaller than the first threshold value and larger than the second threshold value, judging that the physiological parameter value is normal; when the physiological parameter value is smaller than the second threshold value, the physiological parameter value is judged to be too low.
The first indicator is a bar graph.
In the method for analyzing physiological parameter values of the present invention, in the step (b), each pattern is a color.
The invention has the beneficial effects that: the distribution and the change of the blood sugar value of the corresponding event can be easily observed and tracked by the user, so that the medication judgment of the user is further assisted.
Drawings
Other features and effects of the present invention will become apparent from the following detailed description of the embodiments with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart illustrating the steps of a method of analyzing a physiological parameter value of the present invention;
FIG. 2 is a schematic diagram illustrating a plurality of first indicators corresponding to a plurality of event tags, respectively;
FIG. 3 is a schematic diagram illustrating a plurality of second indicators each corresponding to an event tag;
FIG. 4 is a diagram illustrating the blood glucose values corresponding to the event labels and the differences between the blood glucose values corresponding to the event labels having a matching relationship between the blood glucose values and the blood glucose values; and
fig. 5 is a diagram illustrating a trend graph corresponding to the event label.
Detailed Description
The method for analyzing the physiological parameter value is implemented by an electronic device such as a smart phone, and an application program is executed by the electronic device. The electronic device stores a plurality of physiological parameter values, and each physiological parameter value corresponds to one of a plurality of event tags. The physiological parameter value is used as a blood glucose value for explanation, and each event label is one of midnight, morning start, before breakfast, after breakfast, before lunch, after lunch, before dinner, after dinner and before sleeping; in other embodiments, the physiological parameter value may also be, for example, a blood pressure value, a heart rate, or a blood oxygen concentration, and the event label may be, for example, fasting, pre-exercise, post-exercise, pre-or post-medication, etc. Taking "before breakfast" as an example, the user measures his/her blood glucose value before breakfast, and inputs the measured blood glucose value and the corresponding measurement time point into the electronic device through the application program to store and label the event label corresponding to the blood glucose value before breakfast, wherein the label of the event label can be manually input by the user, or the application program automatically judges the event label of the blood glucose value according to the measurement time point, so that the electronic device stores a plurality of blood glucose values measured on different days corresponding to breakfast; the corresponding blood glucose values for the other event labels are generated in a similar manner.
Referring to fig. 1 and 2, the steps of the method for analyzing physiological parameter values according to the present invention are described in detail below.
First, in step 11, for each event label, the electronic device calculates the proportion of the number of excessively high blood glucose levels, the proportion of the number of normal blood glucose levels, and the proportion of the number of excessively low blood glucose levels among the plurality of blood glucose levels corresponding to the event label. Wherein, according to the diagnosis and treatment standard of American Diabetes Association (ADA), for midnight, after breakfast, after lunch and after dinner, the blood sugar value is within the range of 70-140 mg/dL, which is too high if more than 140mg/dL, and too low if less than 70 mg/dL; for morning, before breakfast, before lunch and before dinner, the blood sugar value is within the range of 70-100 mg/dL, which is normal, if the blood sugar value is more than 100mg/dL, the blood sugar value is too high, and if the blood sugar value is less than 70mg/dL, the blood sugar value is too low; before sleep, the blood glucose value is within the range of 70-120 mg/dL, which is normal, if the blood glucose value is more than 120mg/dL, the blood glucose value is too high, and if the blood glucose value is less than 70mg/dL, the blood glucose value is too low. Preferably, the range of blood glucose values that are too high, normal, or too low will vary depending on the diagnosis of the individual patient by the physician.
Next, in step 12, for each event tag, the electronic device generates a first indicator corresponding to the event tag, the first indicator can be a bar graph, a circle graph, a bar graph, a circle graph or a radar graph, but not limited thereto, for example, a bar graph, the first indicator is a first bar graph 3, wherein the first bar graph 3 represents the ratio of the number of too high blood glucose values, the ratio of the number of normal blood glucose values and the ratio of the number of too low blood glucose values in a first pattern, a second pattern and a third pattern respectively, and the length ratios of the first pattern, the second pattern and the third pattern in the first bar graph 3 are respectively the same as the ratio of the number of too high blood glucose values, the ratio of the number of normal blood glucose values and the ratio of the number of too low blood glucose values. Here, each pattern is a color pattern, but the pattern is not limited thereto, and may be a pattern, for example. In addition, when the number proportion of the excessively high blood sugar value, the number proportion of the normally blood sugar value and the number proportion of the excessively low blood sugar value are all larger than zero, the first pattern is adjacent to the second pattern, the second pattern is adjacent to the third pattern, and the first pattern and the third pattern are not adjacent.
For example, fig. 2 shows that the event labels and the first bar graph 3 are displayed on the display screen 2 of the electronic device, wherein each event label corresponds to a blood glucose value stored within 14 days corresponding to the event label, and the first pattern, the second pattern and the third pattern are respectively red 91 (represented by ·), green 92 (represented by +) and blue 93 (represented by L). In particular, the user can observe at a glance from the first long graph 3 that the blood glucose level tends to be too high before and after three meals in the 14 days, wherein the number of occurrences is large after lunch, after dinner and before sleep; the blood sugar values are too low in the middle of the night, before the morning and before three meals, wherein the blood sugar values are more frequently generated in the middle of the night.
Furthermore, in addition to the event label and the first bar graph 3, the electronic device also displays the proportion of blood glucose values that are too high, normal or too low among all blood glucose values for the 14 days, here 24%, 64% and 12%, respectively; among them, blood glucose levels with excessively high blood glucose levels fluctuate between 195-273 mg/dL, blood glucose levels with normal blood glucose levels fluctuate between 93-177 mg/dL, blood glucose levels with excessively low blood glucose levels fluctuate between 55-82 mg/dL, and the severity of blood glucose abnormality can be grasped from the fluctuation range of blood glucose levels.
Even when the glycated hemoglobin concentration (HbA 1 c) is normal, diabetic complications may occur due to a high variation in blood glucose level, and an excessively high or excessively low blood glucose level cannot be distinguished because the glycated hemoglobin concentration is only an average value of blood glucose levels; one of the objectives of diabetes care is to stabilize the blood sugar level within a relatively narrow range, so that the smaller the swing amplitude of the blood sugar level, the better. Through the first long graph 3, the user can easily grasp the event or time period that the blood sugar value is too high or too low during the work and rest of the life, and further adjust the related life habits; the data of the fluctuation range of the blood glucose level can assist in prompting the user of the degree of abnormal blood glucose level.
In addition to observing the distribution of the blood glucose values corresponding to each event label or each time interval within 14 days through the first bar graph 3, the user can also operate the application program every 14 days to generate the first bar graph 3, observe the change of the self blood glucose value between different periods, and track the change of the blood glucose value in 14 days as a period unit; for example, the first bar graph 3 corresponding to the morning beginning in the previous 14 days period shows that the blood sugar values are all normal, while the first bar graph 3 corresponding to the morning beginning in the current 14 days period shows that the blood sugar value is too low, so that the proportion is quite high, and the user or the medical staff can judge that the blood sugar value in the morning beginning in the current 14 days period is abnormal according to the blood sugar value, and further analyze the reason of the abnormal blood sugar value and draw up the blood sugar control plan. Of course, the user can also observe the distribution and variation of blood glucose values in a period unit of 7 days, 30 days or more.
Referring to fig. 3, the user can also operate the application program to switch to another screen 2 by clicking, sliding or other selection means, and for each event label, generate a second indicator corresponding to the event label according to the blood glucose values corresponding to the event label, where the second indicator can be a bar chart, a line chart, a scatter chart or a radar chart, for example, a "bar chart", and the second indicator is the second bar chart 4 shown in fig. 3, where the length of the second bar chart 4 is related to the average value of the blood glucose values corresponding to the event label. In addition, referring to fig. 4, the user can also operate the application program to switch to another screen 2, so that the electronic apparatus displays a plurality of blood glucose values corresponding to each event tag. In contrast to the longitudinal analysis of the blood glucose abnormal ratio and the blood glucose average value, in the blood glucose value shown in fig. 4, under the pairing relationship between the before-meal and the after-meal, when the blood glucose value after the meal minus the blood glucose value before the meal is more than 60mg/dL, the red bottom line 5 represents that the blood glucose rise is too high, and when the blood glucose value after the meal minus the blood glucose value before the meal is less than 30mg/dL, the blue bottom line 6 represents that the blood glucose rise is insufficient, which is a transverse analysis.
Referring to fig. 5, the user may also operate the application to switch to another frame 2, generating a trend graph 7 corresponding to the event label. For each event label, the trend graph 7 represents the newest of all blood glucose values corresponding to the event label with a solid dot 71 and represents a non-newest blood glucose value corresponding to the event label with an open dot 72; when the user clicks the solid dot 71 or the hollow dot 72 by the electronic device, the electronic device further displays related information including a blood glucose level and a measurement time point of the blood glucose level, etc. below the trend graph 7. The trend graph 7 also includes a simple moving average line 73 (i.e., a curve obtained by connecting arithmetic averages of a plurality of blood glucose levels corresponding to the solid dots 71) corresponding to the event label. In addition, the electronic device further displays the time difference 81 and the blood sugar value difference 82 of two events which are in a front-back relationship or adjacent in time. As shown in FIG. 5, the time gap between breakfast and breakfast was 1 hour 48 minutes and the blood glucose level after breakfast was increased by 8mg/dL compared to before breakfast; the time difference between after lunch and before lunch was 2 hours 04 minutes and the blood glucose level after lunch increased 92mg/dL compared to before lunch; the time difference between after dinner and before dinner was 02 minutes for 2 hours and blood glucose levels increased by 29mg/dL after dinner compared to before dinner.
In summary, the method for analyzing physiological parameter values of the present invention defines a plurality of event labels, collects a plurality of physiological parameter values corresponding to the event labels for each event label, calculates a quantity ratio of an excessively high physiological parameter value, a quantity ratio of a normal physiological parameter value, and a quantity ratio of an excessively low physiological parameter value in the physiological parameter values, generates the first indicator and the second indicator corresponding to the event label according to the quantity ratio, and generates the trend graph corresponding to the event label according to the quantity ratio, so that a user can easily observe and track the distribution and the change of the physiological parameter values corresponding to the event, thereby achieving the purpose of the present invention.
The above description is only an example of the present invention, and the scope of the present invention should not be limited thereby, and the invention is still within the scope of the present invention by simple equivalent changes and modifications made according to the claims and the contents of the specification.
Claims (9)
1. A method for analyzing a physiological parameter value, the method being implemented by an electronic device storing a plurality of physiological parameter values corresponding to an event tag, the method comprising: the method for analyzing the physiological parameter value comprises the following steps:
(a) Calculating the quantitative proportion of the physiological parameter values which are too high, the quantitative proportion of the physiological parameter values which are normal and the quantitative proportion of the physiological parameter values which are too low; and
(b) Generating a first indicator corresponding to the event label according to the quantity ratio, wherein the first indicator represents the quantity ratio of the physiological parameter value being too high, the quantity ratio of the physiological parameter value being normal and the quantity ratio of the physiological parameter value being too low in a first pattern, a second pattern and a third pattern respectively, and the size ratios of the first pattern, the second pattern and the third pattern in the first indicator are respectively the same as the quantity ratio of the physiological parameter value being too high, the quantity ratio of the physiological parameter value being normal and the quantity ratio of the physiological parameter value being too low, when the quantity ratio of the physiological parameter value being too high, the quantity ratio of the physiological parameter value being normal and the quantity ratio of the physiological parameter value being too low are all greater than zero, the first pattern is adjacent to the second pattern, the second pattern is adjacent to the third pattern, and the first pattern is not adjacent to the third pattern; and
(c) The physiological parameter values of two adjacent event labels in all the physiological parameter values are paired to be used as a group of pairing relations, the difference of the physiological parameter values in each group of pairing relations is calculated, all the physiological parameter values are displayed, the pairing relations with the difference larger than a first preset difference value are represented by a first mark, and the pairing relations with the difference smaller than a second preset difference value are represented by a second mark.
2. A method of analyzing a value of a physiological parameter according to claim 1, wherein: the physiological parameter value is a blood glucose value, and the event label is one of midnight, morning start, before breakfast, after breakfast, before lunch, after lunch, before dinner, after dinner, before sleeping, fasting, before exercise, after exercise, before taking medicine, and after taking medicine.
3. A method of analyzing a value of a physiological parameter according to claim 1, wherein: further comprising a step (d): generating a second indicator corresponding to the event label based on the value of the physiological parameter, wherein the size of the second indicator positively correlates to the average value of the physiological parameter.
4. A method of analyzing a value of a physiological parameter according to claim 1, wherein: each physiological parameter value corresponds to one of a plurality of event labels, and the method for analyzing the physiological parameter value further comprises a step (e): and generating a trend graph corresponding to the event labels according to the physiological parameter values, wherein the trend graph displays the physiological parameter values corresponding to different event labels.
5. A method of analyzing a value of a physiological parameter according to claim 4, wherein: in this step (e), the trend graph contains a simple moving average corresponding to the event label.
6. A method of analyzing a value of a physiological parameter according to claim 4, wherein: in step (e), for each event label, the trend graph represents, in a first pattern, the most recent of all physiological parameter values corresponding to the event label, and represents, in a second pattern, a non-most recent physiological parameter value corresponding to the event label.
7. A method of analyzing a value of a physiological parameter according to claim 1, wherein: in the step (a), the event label corresponds to a first threshold value and a second threshold value smaller than the first threshold value, and for each physiological parameter value, when the physiological parameter value is larger than the first threshold value, it is determined that the physiological parameter value is too high; when the physiological parameter value is smaller than the first threshold value and larger than the second threshold value, judging that the physiological parameter value is normal; when the physiological parameter value is smaller than the second threshold value, the physiological parameter value is judged to be too low.
8. A method of analyzing a value of a physiological parameter according to claim 1, wherein: the first indicator is a bar graph.
9. A method of analyzing a value of a physiological parameter according to claim 1, wherein: in this step (b), each pattern is a color.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710522331.5A CN109215784B (en) | 2017-06-30 | 2017-06-30 | Method for analyzing physiological parameter values |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710522331.5A CN109215784B (en) | 2017-06-30 | 2017-06-30 | Method for analyzing physiological parameter values |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109215784A CN109215784A (en) | 2019-01-15 |
| CN109215784B true CN109215784B (en) | 2022-11-18 |
Family
ID=64976436
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710522331.5A Active CN109215784B (en) | 2017-06-30 | 2017-06-30 | Method for analyzing physiological parameter values |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109215784B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103210311A (en) * | 2010-12-28 | 2013-07-17 | 泰尔茂株式会社 | Blood glucose measuring device |
| CN105404769A (en) * | 2015-11-02 | 2016-03-16 | 腾讯科技（深圳）有限公司 | Health data display method and device |
| CN105653865A (en) * | 2015-12-31 | 2016-06-08 | 中国科学院深圳先进技术研究院 | Blood glucose monitoring method, device and system |
| CN105745655A (en) * | 2013-09-20 | 2016-07-06 | 赛诺菲-安万特德国有限公司 | Data management unit and method operating same |
| CN105956400A (en) * | 2016-05-06 | 2016-09-21 | 南通大学 | Monitoring and feedback system for self-management compliance of diabetic patient |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101596125A (en) * | 2008-06-06 | 2009-12-09 | 英业达股份有限公司 | A kind of health and fitness information display system, method and interface thereof that possesses demonstration directly perceived |
| EP2333527A4 (en) * | 2008-09-29 | 2012-03-14 | Terumo Corp | Blood sugar information processor, blood sugar information processing method, and blood sugar information processing program |
| CN101789229B (en) * | 2009-01-23 | 2015-03-11 | 理康互联科技(北京)有限公司 | Health information display and control device and method, corresponding equipment and reagent carrier |
| EP2851821A1 (en) * | 2013-09-20 | 2015-03-25 | Sanofi-Aventis Deutschland GmbH | Medical device and method operating same |
| CN113571187A (en) * | 2014-11-14 | 2021-10-29 | Zoll医疗公司 | Medical premonitory event estimation system and externally worn defibrillator |
| KR20160136685A (en) * | 2015-05-20 | 2016-11-30 | 삼성전자주식회사 | Method and apparatus of evaluating exercise capability using heart rate |
-
2017
- 2017-06-30 CN CN201710522331.5A patent/CN109215784B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103210311A (en) * | 2010-12-28 | 2013-07-17 | 泰尔茂株式会社 | Blood glucose measuring device |
| CN105745655A (en) * | 2013-09-20 | 2016-07-06 | 赛诺菲-安万特德国有限公司 | Data management unit and method operating same |
| CN105404769A (en) * | 2015-11-02 | 2016-03-16 | 腾讯科技（深圳）有限公司 | Health data display method and device |
| CN105653865A (en) * | 2015-12-31 | 2016-06-08 | 中国科学院深圳先进技术研究院 | Blood glucose monitoring method, device and system |
| CN105956400A (en) * | 2016-05-06 | 2016-09-21 | 南通大学 | Monitoring and feedback system for self-management compliance of diabetic patient |
Non-Patent Citations (2)
| Title |
|---|
| "细胞生理多参数自动分析仪的软件设计及算法分析";程功 等;《浙江大学学报(工学版)》;20120906;第46卷(第12期);第2285-2292页 * |
| "重症患者床旁指端血糖监测的准确性、一致性评价及影响因素分析";冯涛 等;《实用医学杂志》;20130625;第29卷(第12期);第1969-1971页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109215784A (en) | 2019-01-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8279226B2 (en) | Visualization of a parameter which is measured on the human body | |
| EP2677931B1 (en) | Device and method for determining blood glucose characteristics | |
| EP1754439A1 (en) | Electronic blood pressure monitor, and blood pressure measurement data processing apparatus and method | |
| RU2749187C2 (en) | Computer-implemented method and portable apparatus for analysis of glucose control data indicating glucose level in bodily fluid | |
| US9750423B2 (en) | Method and display for long term physiological signal quality indication | |
| EP3305188A1 (en) | Biosignal measurement device utilizing plurality of electrodes for measuring biosignal as touch sensors | |
| US20130038453A1 (en) | Blood Sugar Level Measuring Apparatus, Blood Sugar Level Measured Result Display Method and Blood Sugar Level Measured Result Display Control Program | |
| JP2010510866A (en) | Method and apparatus for managing glucose control | |
| US9402585B2 (en) | Biological information monitor and biological information monitoring system | |
| US10456087B2 (en) | Method for score confidence interval estimation when vital sign sampling frequency is limited | |
| JP6696962B2 (en) | Data management unit | |
| US20150073754A1 (en) | Method and system for calculating indices for diabetes control | |
| Crenier | Poincaré plot quantification for assessing glucose variability from continuous glucose monitoring systems and a new risk marker for hypoglycemia: application to type 1 diabetes patients switching to continuous subcutaneous insulin infusion | |
| JP2016534841A (en) | Data management unit to support health management | |
| US20170004258A1 (en) | Medical intervention data display for patient monitoring systems | |
| CN109215784B (en) | Method for analyzing physiological parameter values | |
| CN113643820A (en) | Early warning information generation method and device, computer equipment and storage medium | |
| CN108335750B (en) | Method, system and computer storage medium for dynamically analyzing blood glucose values | |
| TWI667012B (en) | Method for analyzing physiological parameter values | |
| US10751005B2 (en) | Vital information monitor | |
| US20130311204A1 (en) | System and method for monitoring patients | |
| CN116685268A (en) | Monitoring system, method for comprehensive management of atrial fibrillation and method for displaying monitored data | |
| CN114569098A (en) | Monitoring system, monitoring equipment and atrial fibrillation presenting method thereof | |
| US20080171912A1 (en) | Basal Blood pressure measuring method | |
| CA2332773A1 (en) | Method and apparatus for background surveillance and detection of unsuspected aberrant clinical information |
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 |