CN115137322A - Continuous monitoring system for dynamic blood pressure - Google Patents
Continuous monitoring system for dynamic blood pressure Download PDFInfo
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- CN115137322A CN115137322A CN202211078107.9A CN202211078107A CN115137322A CN 115137322 A CN115137322 A CN 115137322A CN 202211078107 A CN202211078107 A CN 202211078107A CN 115137322 A CN115137322 A CN 115137322A
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Abstract
The invention discloses a dynamic blood pressure continuous monitoring system, relates to the field of blood pressure monitoring, and is used for solving the problems that the existing blood pressure continuous monitoring system has a single blood pressure detection mode and insufficient safety and brings certain influence on the use of the blood pressure continuous monitoring system; when the environment is abnormal, the system sends out warning information in time to remind a monitored person, and different monitoring modes are formulated according to the physical state of the monitored person, so that personnel in different physical states can be better and more carefully monitored, the physical safety of the monitored person is ensured, the motion state of the monitored person can be detected, the blood pressure state of a user is monitored according to the motion state, corresponding warning information is generated in time to remind the monitored person, the physical safety of the monitored person is better protected, and the system is more worthy of popularization and use. The invention can more comprehensively carry out continuous monitoring on the blood pressure, and the multi-mode blood pressure monitoring can better ensure the body safety of the monitored person.
Description
Technical Field
The invention relates to the field of blood pressure monitoring, in particular to a dynamic blood pressure continuous monitoring system.
Background
When blood flows in a blood vessel, the lateral pressure against the blood vessel wall is called blood pressure. Blood pressure, usually referred to as arterial or systemic blood pressure, is an important vital sign. Blood pressure measurement is the main means for assessing blood pressure level, diagnosing hypertension and observing the curative effect of blood pressure reduction, and accurate blood pressure measurement is the basis of carrying out hypertension management at the basic level. The organic combination of different blood pressure measuring methods is an important factor for improving the diagnosis and management effects of hypertension;
whether the state of the human body is normal or not can be known in time by continuously monitoring the blood pressure of the human body, and a blood pressure continuous monitoring system can be used when the blood pressure of the human body is continuously monitored.
The existing blood pressure continuous monitoring system has a single blood pressure detection mode and is not high enough in safety, and certain influence is brought to the use of the blood pressure continuous monitoring system, so that the dynamic blood pressure continuous monitoring system is provided.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to solve current blood pressure continuous monitoring system, blood pressure detection mode is single and the security is not high enough, has brought the problem of certain influence for blood pressure continuous monitoring system's use, provides a developments blood pressure continuous monitoring system.
The invention solves the technical problems through the following technical scheme, and provides a dynamic blood pressure continuous monitoring system which comprises an acquisition module group, a data receiving module, a data processing module, a master control module and an information sending module; the acquisition module group comprises a human body information acquisition module, a body temperature acquisition module, a position information acquisition module, a heart rate information acquisition module, an environment information acquisition module and a blood pressure acquisition module;
the human body information acquisition module is used for acquiring human body information of a monitored person, the human body information comprises age information, weight information and height information, and the position information acquisition module is used for acquiring real-time position information of the monitored person;
the heart rate information acquisition module is used for acquiring real-time heart rate information of a monitored person, the body temperature information acquisition module is used for acquiring real-time body temperature information of the monitored person, the environment information acquisition module is used for acquiring environment information of the monitored person, the environment information comprises environment air humidity information and noise size information, and the blood pressure acquisition module is used for acquiring environment air humidity information, environment altitude information and environment noise size information of the monitored person;
the data receiving module is used for receiving human body information, real-time position information, real-time heart rate information, real-time body temperature information, environmental information and noise size information, and the data receiving module uploads the received information to a preset terminal for storage and sends the human body information, the real-time position information, the real-time heart rate information, the real-time body temperature information, the environmental information and the noise size information to the data processing module;
the data processing module processes the human body information, the real-time position information, the real-time heart rate information, the real-time body temperature information, the environmental information and the noise size information to generate monitoring mode selection information, environmental assessment information, heart rate warning information, human body warning information and exercise warning information.
The monitoring mode selection information further includes a first monitoring mode, a second monitoring mode and a third monitoring mode, the first acquisition mode, the second monitoring mode and the third monitoring mode are different in blood pressure information acquisition time interval and acquisition times among the first acquisition mode, the second monitoring mode and the third monitoring mode, and the acquisition times are more increased as the blood pressure information acquisition time interval is shorter as the level is higher.
Further, the first monitoring mode, the second monitoring mode and the third monitoring mode are determined and generated as follows: the method comprises the steps of extracting collected human body information, processing the human body information to obtain evaluation parameter information, generating a first monitoring mode when the evaluation parameter information is larger than a preset value A1, generating a second monitoring mode when the evaluation parameter information is between the preset values A1 and A2, and generating a third monitoring mode when the evaluation parameter information is smaller than the preset value A2.
Further, the specific processing procedure of the evaluation parameter information is as follows: extracting the collected human body information, acquiring age information, weight information and height information from the human body information, marking the age information as M, marking the weight information as Q, marking the height information as T, calculating the ratio of the weight information Q to the height information T to obtain a weight coefficient Qt, and giving a corrected value W1 to the weight coefficient Qt, a corrected value W2 to the age information M, W1+ W2=1, W1 > W2 for the importance of the sudden weight coefficient, so that the evaluation parameter information is obtained through a formula Qt W1+ M W2= Qm.
Further, the environmental evaluation information includes excellent environmental information, general environmental information, and hazardous environmental information, and the specific processing procedure is as follows: the method comprises the steps of extracting collected environment information, obtaining environment air humidity information, environment altitude information and environment noise size information from the environment information, marking the environment air humidity information as E1, marking the environment altitude information as E2, marking the environment noise size information as E3, extracting real-time blood pressure information, generating general environment information when the environment air humidity information E1, the environment altitude information E2 and the environment noise size information E3 are all larger than preset values and the real-time blood pressure information is larger than B1, generating general environment information when any two of the environment air humidity information E1, the environment altitude information E2 or the environment noise size information E3 are larger than preset values and the real-time blood pressure information is smaller than B1, generating general environment information when any one of the environment air humidity information E1, the environment altitude information E2 or the environment noise size information E3 is larger than the preset values and the real-time blood pressure information is larger than B1, and generating excellent environment information when the environment air humidity information E1, the environment altitude information E2 and the environment noise size information E3 are all smaller than the preset values and the real-time blood pressure information is smaller than B1.
Further, the specific processing procedure of the heart rate warning information is as follows: extracting and collecting real-time heart rate information, marking the real-time information as Y1, extracting and collecting real-time blood pressure information in real time, marking the real-time blood pressure information as Y2, generating heart rate warning information when the information is larger than a preset value and the real-time blood pressure information Y2 is larger than a preset blood pressure, and generating heart rate warning information when the information is smaller than the preset value and the real-time blood pressure information Y2 is smaller than the preset blood pressure.
Further, the specific processing procedure of the human body warning information is as follows: and extracting the collected real-time body temperature information and real-time blood pressure information, and generating human body warning information when the real-time body temperature information and the real-time blood pressure information are both greater than preset values.
Further, the specific processing procedure of the motion warning information is as follows: the motion state of the monitored person is judged, when the user is judged to be in the motion state, the real-time blood pressure information of the monitored person is collected once every preset time, at least x times of real-time blood pressure information is collected, x is larger than or equal to 5, the blood pressure mean value of the x times of real-time blood pressure information is calculated, and when the blood pressure mean value is larger than a preset value, motion warning information is generated.
Further, the specific process of the motion state determination is as follows: the method comprises the steps of extracting position information of a monitored person adjacent to the monitored person twice, marking the position information as a point J1 and a point J2, respectively extracting time points for obtaining the point J1 and the point J2, marking the time points as a point R1 and a point R2, calculating a difference value between the point R2 and the point R1 to obtain obtaining time length information Rr, measuring distance information between the point J1 and the point J2 to obtain moving distance information Jj, calculating a ratio between the moving distance information Jj and the obtaining time length information Rr to obtain a movement judgment parameter Jr, generating a movement state when the movement judgment parameter Jr is larger than a preset value, and generating a non-movement state when the movement judgment parameter Jr is smaller than the preset value.
Compared with the prior art, the invention has the following advantages: this dynamic blood pressure continuous monitoring system, carry out the integrated processing through the place environment to being monitored the people, can know the influence of environmental condition to user's blood pressure, and when the environment is unusual, timely warning information that sends reminds by being monitored the people, simultaneously according to being made different monitoring modes by monitoring people's health, thereby can be better carry out more careful monitoring to the personnel of different health, guarantee by monitoring people's health, and can detect the motion state by monitoring people, monitor user's blood pressure state according to the motion state, timely generation corresponds warning information, remind by monitoring people, better protection monitoring people's health safety, make this system be worth using widely more.
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FIG. 1 is a system block diagram of the present invention.
Detailed Description
The following examples are given for the detailed implementation and specific operation of the present invention, but the scope of the present invention is not limited to the following examples.
As shown in fig. 1, the present embodiment provides a technical solution: a dynamic blood pressure continuous monitoring system comprises a human body information acquisition module, a body temperature acquisition module, a position information acquisition module, a heart rate information acquisition module, an environment information acquisition module, a blood pressure acquisition module, a data receiving module, a data processing module, a master control module and an information sending module;
the human body information acquisition module is used for acquiring human body information of a monitored person, the human body information comprises age information, weight information and height information, and the position information acquisition module is used for acquiring real-time position information of the monitored person;
the heart rate information acquisition module is used for acquiring real-time heart rate information of a monitored person, the body temperature information acquisition module is used for acquiring real-time body temperature information of the monitored person, the environment information acquisition module is used for acquiring environment information of the monitored person, the environment information comprises environment air humidity information and noise size information, and the blood pressure acquisition module is used for acquiring environment air humidity information, environment altitude information and environment noise size information of the monitored person;
the data receiving module is used for receiving human body information, real-time position information, real-time heart rate information, real-time body temperature information, environmental information and noise size information, uploading the information to a preset terminal for storage after receiving the information, and sending the human body information, the real-time position information, the real-time heart rate information, the real-time body temperature information, the environmental information and the noise size information to the data processing module;
the data processing module processes the human body information, the real-time position information, the real-time heart rate information, the real-time body temperature information, the environmental information and the noise size information to generate monitoring mode selection information, environmental evaluation information, heart rate warning information, human body warning information and exercise warning information;
the invention can know the influence of the environmental state on the blood pressure of the user by comprehensively processing the environment of the monitored person, timely sends out warning information to remind the monitored person when the environment is abnormal, and simultaneously formulates different monitoring modes according to the physical state of the monitored person, thereby better carrying out more detailed monitoring on the persons with different physical states, ensuring the physical safety of the monitored person, detecting the motion state of the monitored person, monitoring the blood pressure state of the user according to the motion state, timely generating corresponding warning information to remind the monitored person, better protecting the physical safety of the monitored person, and leading the system to be more worthy of popularization and use.
The monitoring mode selection information comprises a first monitoring mode, a second monitoring mode and a third monitoring mode, the first acquisition mode, the second monitoring mode and the third monitoring mode are different in blood pressure information acquisition time interval and acquisition frequency among the first acquisition mode, the second monitoring mode and the third monitoring mode, and the lower the level is, the shorter the blood pressure information acquisition time interval is, the more the acquisition frequency is;
through the process, different monitoring requirements can be met by setting various different monitoring modes, and the blood pressure monitoring can be better carried out on the personnel in different states.
The judgment generation process of the first monitoring mode, the second monitoring mode and the third monitoring mode is as follows: the method comprises the steps of extracting collected human body information, processing the human body information to obtain evaluation parameter information, generating a first monitoring mode when the evaluation parameter information is larger than a preset value A1, generating a second monitoring mode when the evaluation parameter information is between the preset values A1 and A2, and generating a third monitoring mode when the evaluation parameter information is smaller than the preset value A2;
through the process, more accurate setting of the monitoring mode can be carried out according to the physical state of the monitored person.
The specific processing procedure for evaluating the parameter information is as follows: extracting the collected human body information, acquiring age information, weight information and height information from the human body information, marking the age information as M, marking the weight information as Q, marking the height information as T, calculating the ratio of the weight information Q to the height information T to obtain a weight coefficient Qt, and giving a corrected value W1 to the weight coefficient Qt, a corrected value W2 to the age information M, W1+ W2=1, W1 > W2 for the importance of a sudden weight coefficient, so that evaluation parameter information is obtained through a formula Qt W1+ M W2= Qm;
more accurate evaluation parameter information can be acquired through the process.
The environmental evaluation information includes excellent environmental information, general environmental information and dangerous environmental information, and the specific processing procedure is as follows: extracting collected environment information, acquiring environment air humidity information, environment altitude information and environment noise size information from the environment information, marking the environment air humidity information as E1, marking the environment altitude information as E2, marking the environment noise size information as E3, extracting real-time blood pressure information, generating general environment information when the environment air humidity information E1, the environment altitude information E2 and the environment noise size information E3 are all larger than a preset value and the real-time blood pressure information is larger than B1, generating general environment information when any two of the environment air humidity information E1, the environment altitude information E2 or the environment noise size information E3 are larger than the preset value and the real-time blood pressure information is smaller than B1, generating general environment information when any one of the environment air humidity information E1, the environment altitude information E2 or the environment noise size information E3 is larger than the preset value and the real-time blood pressure information is larger than B1, and generating excellent environment information when the environment air humidity information E1, the environment altitude information E2 and the environment noise size information E3 are all smaller than the preset value and the real-time blood pressure information is smaller than B1;
through the process, the environment where the monitored person is located is comprehensively processed, the influence of the environment state on the blood pressure of the user can be known, and when the environment is abnormal, warning information is timely sent out to remind the monitored person, so that the damage of the environment abnormality to the monitored person is reduced.
The specific processing process of the heart rate warning information is as follows: extracting the collected real-time heart rate information, marking the real-time information as Y1, extracting the real-time blood pressure information collected in real time, marking the real-time blood pressure information as Y2, generating heart rate warning information when the information is greater than a preset value and the real-time blood pressure information Y2 is greater than a preset blood pressure, and generating heart rate warning information when the information is less than the preset value and the real-time blood pressure information Y2 is less than the preset blood pressure;
through the heart rate warning information who sets up, can be in time send warning information when monitoring people's heart rate and blood pressure are unusual, avoid unexpected the emergence.
The specific processing process of the human body warning information is as follows: and extracting the collected real-time body temperature information and real-time blood pressure information, and generating human body warning information when the real-time body temperature information and the real-time blood pressure information are both greater than preset values.
The specific processing procedure of the motion warning information is as follows: judging the motion state of the monitored person, when the user is judged to be in the motion state, acquiring the real-time blood pressure information of the monitored person once every preset time, acquiring the real-time blood pressure information at least x times, wherein x is more than or equal to 5, calculating the blood pressure mean value of the real-time blood pressure information x times, and generating motion warning information when the blood pressure mean value is more than a preset value;
the motion state of the monitored person can be detected through the process, the blood pressure state of the user is monitored according to the motion state, the corresponding warning information is generated in time to remind the monitored person, and the body safety of the monitored person is better protected.
The specific process of motion state determination is as follows: extracting position information of two adjacent monitored persons, marking the position information as a point J1 and a point J2, respectively extracting time points for acquiring the point J1 and the point J2, marking the time points as a point R1 and a point R2, calculating a difference value between the point R2 and the point R1 to obtain acquisition time length information Rr, measuring distance information between the point J1 and the point J2 to obtain movement distance information Jj, calculating a ratio between the movement distance information Jj and the acquisition time length information Rr to obtain a movement judgment parameter Jr, generating a movement state when the movement judgment parameter Jr is greater than a preset value, and generating a non-movement state when the movement judgment parameter Jr is less than the preset value;
through the above process, more accurate judgment of the motion state can be performed.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (7)
1. A dynamic blood pressure continuous monitoring system comprises an acquisition module group, a data receiving module and a monitoring module group, wherein the acquisition module group is used for acquiring monitoring data and sending the monitoring data to the data receiving module; the system is characterized by also comprising a data processing module, a master control module and an information sending module;
the data receiving module is used for receiving monitoring data, uploading the monitoring data to a preset terminal for storage and sending the monitoring data to the data processing module;
the data processing module processes the monitoring data to generate monitoring mode selection information, environment assessment information, heart rate warning information, human body warning information and exercise warning information; the monitoring data comprises human body information, real-time position information, real-time heart rate information, real-time body temperature information, environmental information and noise size information;
the specific processing process of the motion warning information is as follows: judging the motion state of the monitored person, when the user is judged to be in the motion state, acquiring the real-time blood pressure information of the monitored person once every preset time, acquiring the real-time blood pressure information at least x times, wherein x is more than or equal to 5, calculating the blood pressure mean value of the real-time blood pressure information x times, and generating motion warning information when the blood pressure mean value is more than a preset value;
the specific process of judging the motion state is as follows: the method comprises the steps of extracting position information of a monitored person adjacent to the monitored person twice, marking the position information as a point J1 and a point J2, respectively extracting time points for obtaining the point J1 and the point J2, marking the time points as a point R1 and a point R2, calculating a difference value between the point R2 and the point R1 to obtain obtaining time length information Rr, measuring distance information between the point J1 and the point J2 to obtain moving distance information Jj, calculating a ratio between the moving distance information Jj and the obtaining time length information Rr to obtain a movement judgment parameter Jr, generating a movement state when the movement judgment parameter Jr is larger than a preset value, and generating a non-movement state when the movement judgment parameter Jr is smaller than the preset value.
2. The continuous ambulatory blood pressure monitoring system as set forth in claim 1, wherein: the monitoring mode selection information comprises a first monitoring mode, a second monitoring mode and a third monitoring mode, the first acquisition mode, the second monitoring mode and the third monitoring mode are different in blood pressure information acquisition time interval and acquisition times among the first acquisition mode, the second monitoring mode and the third monitoring mode, and the lower the level, the shorter the blood pressure information acquisition time interval is, the more the acquisition times are.
3. A continuous ambulatory blood pressure monitoring system as set forth in claim 2, wherein: the first monitoring mode, the second monitoring mode and the third monitoring mode are determined and generated as follows: the method comprises the steps of extracting collected human body information, processing the human body information to obtain evaluation parameter information, generating a first monitoring mode when the evaluation parameter information is larger than a preset value A1, generating a second monitoring mode when the evaluation parameter information is between the preset values A1 and A2, and generating a third monitoring mode when the evaluation parameter information is smaller than the preset value A2.
4. A continuous ambulatory blood pressure monitoring system as set forth in claim 3, wherein: the specific processing procedure of the evaluation parameter information is as follows: extracting the collected human body information, acquiring age information, weight information and height information from the human body information, marking the age information as M, marking the weight information as Q, marking the height information as T, calculating the ratio of the weight information Q to the height information T to obtain a weight coefficient Qt, and giving a corrected value W1 to the weight coefficient Qt, a corrected value W2 to the age information M, W1+ W2=1, W1 > W2 for the importance of the sudden weight coefficient, so that the evaluation parameter information is obtained through a formula Qt W1+ M W2= Qm.
5. The continuous ambulatory blood pressure monitoring system as set forth in claim 1, wherein: the environment evaluation information comprises excellent environment information, general environment information and dangerous environment information, and the specific processing procedures are as follows: the method comprises the steps of extracting collected environment information, obtaining environment air humidity information, environment altitude information and environment noise size information from the environment information, marking the environment air humidity information as E1, marking the environment altitude information as E2, marking the environment noise size information as E3, extracting real-time blood pressure information, generating general environment information when the environment air humidity information E1, the environment altitude information E2 and the environment noise size information E3 are all larger than preset values and the real-time blood pressure information is larger than B1, generating general environment information when any two of the environment air humidity information E1, the environment altitude information E2 or the environment noise size information E3 are larger than preset values and the real-time blood pressure information is smaller than B1, generating general environment information when any one of the environment air humidity information E1, the environment altitude information E2 or the environment noise size information E3 is larger than the preset values and the real-time blood pressure information is larger than B1, and generating excellent environment information when the environment air humidity information E1, the environment altitude information E2 and the environment noise size information E3 are all smaller than the preset values and the real-time blood pressure information is smaller than B1.
6. The continuous ambulatory blood pressure monitoring system as set forth in claim 1, wherein: the specific processing process of the heart rate warning information is as follows: extracting and collecting real-time heart rate information, marking the real-time information as Y1, extracting and collecting real-time blood pressure information in real time, marking the real-time blood pressure information as Y2, generating heart rate warning information when the information is larger than a preset value and the real-time blood pressure information Y2 is larger than a preset blood pressure, and generating heart rate warning information when the information is smaller than the preset value and the real-time blood pressure information Y2 is smaller than the preset blood pressure.
7. The continuous ambulatory blood pressure monitoring system as set forth in claim 1, wherein said continuous ambulatory blood pressure monitoring system further comprises: the specific processing process of the human body warning information is as follows: and extracting the collected real-time body temperature information and real-time blood pressure information, and generating human body warning information when the real-time body temperature information and the real-time blood pressure information are both greater than preset values.
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Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202282004U (en) * | 2011-06-02 | 2012-06-20 | 上海巨浪信息科技有限公司 | Mobile health management system based on context awareness and activity analysis |
| CN102499660A (en) * | 2011-09-28 | 2012-06-20 | 中山市创源电子有限公司 | Sphygmomanometer for dynamic monitoring of blood pressure |
| JP2014230671A (en) * | 2013-05-29 | 2014-12-11 | 学校法人 関西大学 | Blood pressure estimation device, blood pressure estimation system, and control program |
| CN204033326U (en) * | 2014-04-23 | 2014-12-24 | 深圳星脉医疗仪器有限公司 | With the sphygomanometer of position information data collection and analysis |
| JP2018140172A (en) * | 2017-02-28 | 2018-09-13 | 株式会社Ｎｔｔドコモ | Data collection device and data collection method |
| CN109528183A (en) * | 2019-01-15 | 2019-03-29 | 浙江强脑科技有限公司 | Human body abnormality monitoring method, equipment and computer readable storage medium |
| WO2019089919A2 (en) * | 2017-11-01 | 2019-05-09 | Daniel Shen | Systems and methods for tissue characterization |
| CN110322947A (en) * | 2019-06-14 | 2019-10-11 | 电子科技大学 | A kind of hypertension the elderly's exercise prescription recommended method based on deep learning |
| US10825564B1 (en) * | 2017-12-11 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Biometric characteristic application using audio/video analysis |
| WO2021032320A1 (en) * | 2019-08-20 | 2021-02-25 | David Boeger | Apparatus for influencing body tissue, method for measuring and evaluating a body tissue condition |
| WO2021061314A1 (en) * | 2019-09-26 | 2021-04-01 | DawnLight Technologies Inc. | Dynamic metabolic rate estimation |
| CN113098971A (en) * | 2021-04-12 | 2021-07-09 | 深圳市景新浩科技有限公司 | Electronic blood pressure counting data transmission monitoring system based on internet |
| CN113499047A (en) * | 2021-06-30 | 2021-10-15 | 湖北智奥物联网科技有限公司 | Dynamic blood pressure continuous monitoring device, storage medium and system |
| CN216629572U (en) * | 2021-11-30 | 2022-05-31 | 迈德医疗科技(深圳)有限公司 | Pressure reduction system and equipment based on respiratory training method |
-
2022
- 2022-09-05 CN CN202211078107.9A patent/CN115137322B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202282004U (en) * | 2011-06-02 | 2012-06-20 | 上海巨浪信息科技有限公司 | Mobile health management system based on context awareness and activity analysis |
| CN102499660A (en) * | 2011-09-28 | 2012-06-20 | 中山市创源电子有限公司 | Sphygmomanometer for dynamic monitoring of blood pressure |
| JP2014230671A (en) * | 2013-05-29 | 2014-12-11 | 学校法人 関西大学 | Blood pressure estimation device, blood pressure estimation system, and control program |
| CN204033326U (en) * | 2014-04-23 | 2014-12-24 | 深圳星脉医疗仪器有限公司 | With the sphygomanometer of position information data collection and analysis |
| JP2018140172A (en) * | 2017-02-28 | 2018-09-13 | 株式会社Ｎｔｔドコモ | Data collection device and data collection method |
| WO2019089919A2 (en) * | 2017-11-01 | 2019-05-09 | Daniel Shen | Systems and methods for tissue characterization |
| US10825564B1 (en) * | 2017-12-11 | 2020-11-03 | State Farm Mutual Automobile Insurance Company | Biometric characteristic application using audio/video analysis |
| CN109528183A (en) * | 2019-01-15 | 2019-03-29 | 浙江强脑科技有限公司 | Human body abnormality monitoring method, equipment and computer readable storage medium |
| CN110322947A (en) * | 2019-06-14 | 2019-10-11 | 电子科技大学 | A kind of hypertension the elderly's exercise prescription recommended method based on deep learning |
| WO2021032320A1 (en) * | 2019-08-20 | 2021-02-25 | David Boeger | Apparatus for influencing body tissue, method for measuring and evaluating a body tissue condition |
| WO2021061314A1 (en) * | 2019-09-26 | 2021-04-01 | DawnLight Technologies Inc. | Dynamic metabolic rate estimation |
| CN113098971A (en) * | 2021-04-12 | 2021-07-09 | 深圳市景新浩科技有限公司 | Electronic blood pressure counting data transmission monitoring system based on internet |
| CN113499047A (en) * | 2021-06-30 | 2021-10-15 | 湖北智奥物联网科技有限公司 | Dynamic blood pressure continuous monitoring device, storage medium and system |
| CN216629572U (en) * | 2021-11-30 | 2022-05-31 | 迈德医疗科技(深圳)有限公司 | Pressure reduction system and equipment based on respiratory training method |
Non-Patent Citations (2)
| Title |
|---|
| BJORN, M; SIMONSEN, JW AND MOGENSEN, CB: "A combination of clinical parameters and blood-gas analysis identifies patients at risk of transfer to intensive care upon arrival to the Emergency Department", 《EUROPEAN JOURNAL OF EMERGENCY MEDICINE》 * |
| 马青 等: "109例直接血压与间接血压差值相关性及其影响因素的分析", 《中国民康医学》 * |
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