CN205094444U - Detecting system is fallen down in real time to cloud - Google Patents
Detecting system is fallen down in real time to cloud Download PDFInfo
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- CN205094444U CN205094444U CN201520830709.4U CN201520830709U CN205094444U CN 205094444 U CN205094444 U CN 205094444U CN 201520830709 U CN201520830709 U CN 201520830709U CN 205094444 U CN205094444 U CN 205094444U
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Abstract
The utility model discloses a detecting system is fallen down in real time to cloud, including collection system, the mobile terminal that is connected with collection system, the transfer device of being connected with collection system, mobile terminal respectively, the cloud service platform who is connected with the transfer device to reach the monitor terminal who is connected with cloud service platform, collection system includes the controller, the triaxial acceleration sensor, three -axis gyroscope, body temperature sensor, rhythm of the heart sensor, pulse sensor, blood pressure transducer, orientation module, communication module and the storage module that are connected with the controller respectively. The utility model discloses a collection system, mobile terminal, transfer device form a stable data communication mode, pass to the cloud platform with monitoring target's the information of falling down number of pass on according to the transfer device, realize to monitoring target fall down fast with the real -time supervision of the slow circumstances, this data communication mode can realize functions such as the hierarchy treatment, storage of data, has improved the integrality and the reliability of data greatly.
Description
Technical field
This utility model belongs to monitoring and the identification of human motion behavior, state etc., is specifically related to a kind of cloud service and falls down detection system in real time.
Background technology
With advancing age, the metabolism of people slows down slowly, bradykinesia, and physical function declines, and is easy to fall down.According to statistics, in the elderly population of over-65s, have the people more than 1/3 all can experience every year and fall down, and the old people of nearly 1/4 fall down occur in latter 1 year dead.According to incompletely statistics, in old people's unexpected death, because old people falls down, murderous ratio is up to 2/3, and in old man, this ratio is especially up to 70% more than 75 years old, for Female elderly, the highest because falling down murderous ratio.The Retarder theory caused because of chronic diseases such as cardiovascular is fallen down and has been accounted for 60%, but relevant research is almost nil.Falling over of human body is detected, is generally divided into view-based access control model and based on Wearable sensor two kinds, wherein, adopt vision to carry out falling over of human body detection and seriously can be subject to external environment impact, such as illumination condition, background, block size and video camera quality etc.; In addition, because video camera monitored area is limited, monitored old people or the range of activity of patient can be restricted, in the research utilizing Wearable sensor for human detection to fall down, a kind of is the acceleration adopting the activity of accelerometer human body, whether fallen down by setting threshold decision, this method is difficult to distinguish, as jumped, above going downstairs if falling down the aggravating activities daily with people.As CN201126620Y, CN101650869B is that employing three axis accelerometer records human body acceleration, calculated angle of inclination simultaneously, the former judges whether to fall down by setting acceleration and angle threshold, be difficult to distinguish the vigorous motion such as walking and stair activity fast, the latter judges that the angular relationship that people is subject to impacting front and back a period of time in the process of falling down judges whether to fall down, the method requires that obviously impacting appears in falling over of human body process, be difficult to identify that old people falls in a swoon suddenly or falls down by a small margin, and, its angle is obtained by acceleration calculation, obviously, the angle of inclination calculated when human body aggravating activities or vibrations interference there will be severe deviations, discrimination meeting degradation, another kind is that set angle threshold value and time threshold judge whether to fall down by Wearable angular transducer human body trunk angle, and the method is difficult to that differentiation is bent over, the normal behaviour action such as lie low.Again such as, CN200941648Y and CN2909416Y judges whether to fall down by the inclined degree of sensor for human detection, the actions such as very difficult differentiation is bent over, lie low, in addition, because fall events randomness is strong, and various informative, therefore, the False Rate of this determination methods is higher, and very unstable.
Summary of the invention
The purpose of this utility model is to provide a kind of cloud service and falls down detection system in real time, and that accurately can detect tested personnel falls down situation, and to its real-time track and localization, can also improve the warning accuracy rate of falling down monitoring, avoid failing to report police.
Cloud service described in the utility model falls down detection system in real time, comprise harvester, the mobile terminal be connected with harvester, the transferring device be connected with harvester, mobile terminal respectively, the cloud service platform be connected with transferring device, and the monitor terminal be connected with cloud service platform;
Described harvester comprises controller, the 3-axis acceleration sensor be connected with controller respectively, three-axis gyroscope, body temperature trans, heart rate sensor, pulse transducer, pressure transducer, locating module, communication module and memory module.
Described harvester is arranged on clothes, wherein:
Described heart rate sensor is arranged on the chest locations place of the corresponding human body of clothes;
Described body temperature trans is arranged on the transaxillary position place of the corresponding human body of clothes;
Described pressure transducer is arranged on the elbow position of the corresponding human body of clothes;
Described pulse transducer is arranged on the corresponding human heart position of clothes;
Described 3-axis acceleration sensor, three-axis gyroscope are located before being arranged on the positive breast abdomen of corresponding human body respectively.
Described harvester is worn in wrist.
Also comprise video acquisition device, this video acquisition terminal is connected with transferring device, mobile terminal respectively.
Described harvester also comprises the pressure transducer be connected with controller, and this pressure transducer is arranged in footwear.
Described harvester also comprises the alarm button be connected with controller, and length clicks initiative alarming, double-clicks expression false alarm soon.
This utility model has the following advantages:
(1) be combined with three-axis gyroscope by three axle acceleration of gravitys, all attitudes of human body can be judged, just can know whether tested personnel falls down behavior exactly by the human body physiological parameter changing value of tested personnel again, and whether this behavior of falling down is slowly fall down, avoids misreport of system police and fail to report police;
(2) a stable data communication mode (mode that namely triangle data is mutual) is formed by harvester, mobile terminal, transferring device, the information of falling down of monitoring target is uploaded to cloud platform by data relay device, realizes falling down the Real-Time Monitoring with slow situation fast to monitoring target; This data communication mode can realize the function such as layered shaping, storage of data, substantially increases integrity and the reliability of data;
(3) there is the cloud service platform of concrete management, use for medical and nursing work and family;
(4) cloud service platform has learning functionality, can adjust each judgment threshold, make judgement more accurate according to the Data Dynamic of actual acquisition;
In sum, native system can detect that tested personnel's falls down situation exactly, and possess intellectual learning algorithm, be applicable to various types ofly founder detection, care provider can locate tested personnel's real-time tracking whenever and wherever possible, alarm device can remind related personnel to give first aid in time, greatly reducing the serious consequence that old people or patient cause because of falling down, there is very strong practical value, and system is easy to use, accuracy rate is high, and stability is strong.
Accompanying drawing explanation
Fig. 1 is structured flowchart of the present utility model;
Fig. 2 is the structured flowchart of harvester in this utility model;
Fig. 3 is the drainage pattern figure in this utility model;
Fig. 4 is the structured flowchart of cloud service platform in this utility model.
Detailed description of the invention
Below in conjunction with accompanying drawing, the utility model is described in further detail:
Cloud service as shown in Figure 1 falls down detection system in real time, comprise harvester 1, the mobile terminal 2 be connected with harvester 1, the transferring device 4 be connected with harvester 1, mobile terminal 2 respectively, the cloud service platform 5 be connected with transferring device 4, and the monitor terminal 6 be connected with cloud service platform 5.
Transferring device 4 is hops of whole system, and it receives the acquired signal to harvester 1, and acquired signal is sent to cloud service platform 5, and monitoring personnel access the physiological parameter data in cloud service platform 5 by monitor terminal 6.Transferring device 4 receives the next data to harvester 1 with harvester 1 by short-distance transmission mode, and these data are transferred to cloud service platform 5 by the Internet, 3G, 4G etc.When mobile terminal 2 is in the certain limit of transferring device 4, transferring device 4 carries out the information interaction of physiological parameter by with mobile terminal 2.
Mobile terminal 2 wireless connections are in described harvester 1 or carry out wireless adaptation via WLAN with described transferring device 4 and be connected, and monitored display for the data to be monitored that obtain in described harvester 1 or transferring device 4.
As shown in Figure 2, described harvester 1 comprises controller 13, the 3-axis acceleration sensor 7 be connected with controller 13 respectively, three-axis gyroscope 8, body temperature trans 9, heart rate sensor 10, pulse transducer 11, pressure transducer 12, locating module 14, communication module 15, memory module 16 and alarm module 17.When communicating normal, gathered data are sent to cloud service platform 5 by transferring device 4 by harvester 1, and when occurring abnormal when communicating, gathered data are stored in memory module 16 by harvester 1, again by transferring device 4 after recovery to be communicated is normal; After transferring device 4 receives signal, when communicating normal, data being sent to cloud service platform 5, if communication occurs abnormal, then data being stored in the memorizer of transferring device 4, after recovery to be communicated is normal, send signal to cloud service platform 5 again.After cloud platform receives signal, signal is carried out cloud computing process and storage, facilitate care provider to access real time data.
Further, described harvester 1 also comprises the pressure transducer 22 with controller 13 wireless connections, and this pressure transducer 22 is arranged in footwear, for gathering the pressure value P of sole to ground.
Described harvester 1 is for gathering accekeration, attitude angle, pressure value, body temperature value, heart rate value, the pulse value of human body, described acquisition terminal calculates accekeration a and attitude angle Ψ based on the data that 3-axis acceleration sensor 7 and three-axis gyroscope gather, and calculate the physiological parameter changing value Δ φ of human body before and after falling down based on gathered pressure value, body temperature value, heart rate value, pulse value, and by pressure value P and the pressure threshold P preset
1compare, will speed up angle value a and the first acceleration rate threshold a preset
1with the second acceleration rate threshold a
2compare, attitude angle Ψ and the attitude angle threshold range Δ Ψ preset are compared, the threshold range ΔΦ of human body at the physiological parameter changing value Δ φ and default physiological parameter changing value that fall down front and back is compared, judge whether human body falls down behavior, when judging that human body falls down behavior, described controller 13 triggered location module 14 positions, and locating information is sent to the monitor terminal bound mutually with described acquisition terminal.
As shown in Figure 3, the drainage pattern of described harvester 1 is divided into three kinds, be respectively normal acquisition, abnormal collection and instruction acquisition, described normal acquisition pattern is that described harvester 1 gathers each physiological parameter in set time every day according to the state of tested personnel, and harvester 1 is transferred to transferring device 4 and mobile terminal 2 after carrying out pretreatment to the data gathered respectively.The Monitoring Data appearance exception of tested personnel is judged in described abnormal collection during for controller 13, the physiological parameter of triggering collection system to tested personnel gathers.The single or multiple physiological parameters of the acquisition instructions collection human body that described instruction acquisition sends according to mobile terminal 2 for described harvester 1, harvester 1 does not process the data gathered, and directly uploads remote monitoring center by transferring device 4.Above three kinds of drainage patterns are mutual exclusions, and namely when a kind of acquisition mode carries out, all the other two kinds of acquisition modes can not trigger.The state that often kind of acquisition mode can be according to system adjusts, when harvester 1 receives acquisition instructions, and harvester 1 entry instruction drainage pattern; If when not receiving acquisition instructions, harvester 1 can determine acquisition mode according to the situation of image data, and when the data gathered are normal, harvester 1 enters normal acquisition state; Otherwise harvester 1 enters abnormal acquisition state.
Described cloud service platform 5 for storing gathered data, manage, and constantly learns based on gathered data, obtains the first optimum acceleration rate threshold a
1, the second acceleration rate threshold a
2, attitude angle threshold range Δ Ψ and physiological parameter changing value threshold range ΔΦ.
As shown in Figure 4, described cloud service platform 5 comprises cloud computing module 18, cloud memory module 19, cloud administration module 20 and reports to the police and decision-making module 21.
Described cloud computing module 18 calculates for the large data of the physiological parameter to tested personnel, comprises the collection of user base information, arrangement, statistics, and user's physiological feature is analyzed, statistics, healthy trend prediction.
Described cloud memory module 19, for the distributed storage of all data to tested personnel, comprises all data gathered tested personnel, and the Back ground Information of tested personnel stores.
Described cloud administration module 20, for the management to Monitoring Data, comprises expert diagnosis, health control and health supervision.
The threshold value that described warning and decision-making module 21 comprise warning algorithm determines that (dynamically), tested personnel's health status (normal, early warning, warning) are determined, the decision-making treatment of early warning and alarm condition, as mobile phone short message notice, medical care etc.
Described harvester 1, also based on the acquisition instructions that mobile terminal 2 and monitor terminal 6 send, gathers the single or multiple physiological parameters of human body.Described mobile terminal 2 has Realtime Alerts, the functions such as display.Receive the physiological parameter signals that harvester 1 transmits.When docking successfully with transferring device 4, carry out information exchange by the mode of short-distance transmission.And there is Speech input and video acquisition function.
Harvester 1 described in this utility model is except pressure transducer 22, and remainder is arranged on clothes or integrates and is worn in wrist.When the remainder of harvester 1 is arranged on clothes, described heart rate sensor 10 is arranged on the chest locations place of the corresponding human body of clothes; Described body temperature trans 9 is arranged on the transaxillary position place of the corresponding human body of clothes; Described pressure transducer is arranged on the elbow position of the corresponding human body of clothes; Described pulse transducer 11 is arranged on the corresponding human heart position of clothes; Described 3-axis acceleration sensor 7, three-axis gyroscope 8 are located before being arranged on the positive breast abdomen of corresponding human body respectively.
Further, this utility model also comprises video acquisition device 1, this video acquisition terminal 3 is connected with transferring device 4, mobile terminal 2 respectively, generally video acquisition terminal 3 is arranged on family, when monitoring tested personnel and being in the space that video acquisition device 1 can gather, described mobile terminal 2 and monitor terminal energy triggering video harvester 1 gather current video signal, and feed back to mobile terminal 2 and monitor terminal 6 carries out Real time displaying.
Further, described harvester 1 also comprises the alarm button 23 be connected with controller 13, and when needs initiative alarming, length clicks alarm button 23.When false alarm appears in system, double-click alarm button 23 soon, monitor terminal 6 will know that this is reported to the police as false alarm.
Claims (6)
1. a cloud service falls down detection system in real time, it is characterized in that: comprise harvester (1), the mobile terminal (2) be connected with harvester (1), the transferring device (4) be connected with harvester (1), mobile terminal (2) respectively, the cloud service platform (5) be connected with transferring device (4), and the monitor terminal (6) be connected with cloud service platform (5);
Described harvester (1) comprises controller (13), the 3-axis acceleration sensor (7) be connected with controller (13) respectively, three-axis gyroscope (8), body temperature trans (9), heart rate sensor (10), pulse transducer (11), pressure transducer (12), locating module (14), communication module (15) and memory module (16).
2. cloud service according to claim 1 falls down detection system in real time, it is characterized in that: described harvester (1) is arranged on clothes, wherein:
Described heart rate sensor (10) is arranged on the chest locations place of the corresponding human body of clothes;
Described body temperature trans (9) is arranged on the transaxillary position place of the corresponding human body of clothes;
Described pressure transducer (12) is arranged on the elbow position of the corresponding human body of clothes;
Described pulse transducer (11) is arranged on the corresponding human heart position of clothes;
Described 3-axis acceleration sensor (7), three-axis gyroscope (8) are located before being arranged on the positive breast abdomen of corresponding human body respectively.
3. cloud service according to claim 1 falls down detection system in real time, it is characterized in that: described harvester (1) is worn in wrist.
4. fall down detection system in real time according to the arbitrary described cloud service of claims 1 to 3, it is characterized in that: also comprise video acquisition device (1), this video acquisition terminal (3) is connected with transferring device (4), mobile terminal (2) respectively.
5. fall down detection system in real time according to the arbitrary described cloud service of claims 1 to 3, it is characterized in that: described harvester also comprises the pressure transducer (22) be connected with controller (13), and this pressure transducer (22) is arranged in footwear.
6. fall down detection system in real time according to the arbitrary described cloud service of claims 1 to 3, it is characterized in that: described harvester (1) also comprises the alarm button (23) be connected with controller (13).
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201520830709.4U CN205094444U (en) | 2015-10-26 | 2015-10-26 | Detecting system is fallen down in real time to cloud |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201520830709.4U CN205094444U (en) | 2015-10-26 | 2015-10-26 | Detecting system is fallen down in real time to cloud |
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| Publication Number | Publication Date |
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| CN205094444U true CN205094444U (en) | 2016-03-23 |
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| CN201520830709.4U Expired - Fee Related CN205094444U (en) | 2015-10-26 | 2015-10-26 | Detecting system is fallen down in real time to cloud |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106205051A (en) * | 2016-09-09 | 2016-12-07 | 河北地质大学 | A kind of fall detection emergency treatment alarm based on cloud computing |
| CN108399714A (en) * | 2018-05-10 | 2018-08-14 | 吉林建筑大学 | A kind of smart home fall monitoring alarm system |
| CN108737785A (en) * | 2018-05-21 | 2018-11-02 | 北京奇伦天佑创业投资有限公司 | Indoor tumble automatic checkout system based on TOF 3D video cameras |
| CN108961458A (en) * | 2018-08-29 | 2018-12-07 | 中煤科工集团重庆设计研究院有限公司 | A kind of wearable patrol system |
| US11116424B2 (en) | 2016-08-08 | 2021-09-14 | Koninklijke Philips N.V. | Device, system and method for fall detection |
-
2015
- 2015-10-26 CN CN201520830709.4U patent/CN205094444U/en not_active Expired - Fee Related
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11116424B2 (en) | 2016-08-08 | 2021-09-14 | Koninklijke Philips N.V. | Device, system and method for fall detection |
| CN106205051A (en) * | 2016-09-09 | 2016-12-07 | 河北地质大学 | A kind of fall detection emergency treatment alarm based on cloud computing |
| CN108399714A (en) * | 2018-05-10 | 2018-08-14 | 吉林建筑大学 | A kind of smart home fall monitoring alarm system |
| CN108737785A (en) * | 2018-05-21 | 2018-11-02 | 北京奇伦天佑创业投资有限公司 | Indoor tumble automatic checkout system based on TOF 3D video cameras |
| CN108737785B (en) * | 2018-05-21 | 2020-07-03 | 北京奇伦天佑创业投资有限公司 | Indoor automatic detection system that tumbles based on TOF 3D camera |
| CN108961458A (en) * | 2018-08-29 | 2018-12-07 | 中煤科工集团重庆设计研究院有限公司 | A kind of wearable patrol system |
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