CN104490401A - Method for intelligent terminal for automatically recognizing human behaviors based on acceleration data - Google Patents
Method for intelligent terminal for automatically recognizing human behaviors based on acceleration data Download PDFInfo
- Publication number
- CN104490401A CN104490401A CN201510020940.1A CN201510020940A CN104490401A CN 104490401 A CN104490401 A CN 104490401A CN 201510020940 A CN201510020940 A CN 201510020940A CN 104490401 A CN104490401 A CN 104490401A
- Authority
- CN
- China
- Prior art keywords
- intelligent terminal
- human body
- acceleration
- body behavior
- acceleration information
- 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.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
- A61B5/1116—Determining posture transitions
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
- A61B5/1116—Determining posture transitions
- A61B5/1117—Fall detection
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
- A61B5/112—Gait analysis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Physiology (AREA)
- Surgery (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a method for an intelligent terminal for automatically recognizing human behaviors based on acceleration data and relates to the technical field of human behavior monitoring. The method for the intelligent terminal for automatically recognizing human behaviors based on the acceleration data is capable of automatically recognizing the human behavior type through analyzing the human behavior acceleration data, wherein the human behavior type comprises standing uprightly or lying, sitting up or standing, resting or moving, falling down and the like. Through using the method for the intelligent terminal for automatically recognizing human behaviors based on the acceleration data, the intelligent terminal does not need to set behavior modes in advance and is capable of directly gathering the behavior data of old people and automatically recognizing the human behaviors so as to solve the problem that the old people easily forget setting modes in the intelligent terminal use process, the old people are happy to wear and use the intelligent terminal, the precise and complete data gathering is guaranteed, and the popularization of the intelligent terminal is guaranteed.
Description
Technical field
The present invention relates to human body behavior monitoring technical field, particularly relate to a kind of intelligent terminal based on acceleration information and carry out human body behavior and automatically know method for distinguishing.
Background technology
Now, along with being on the increase of Empty nest elderly, society also gets more and more to the concern of Empty nest elderly and love, relevant also getting more and more for the product gathering old man's behavioral data on market, such as intelligent watch and Intelligent bracelet etc.
At present, to the product that human body behavior is monitored, behavioral data under mainly using acceleration transducer to gather AD HOC, and the data of collection are sent to supervisor timely, occur reporting to the police timely when the hazardous act such as to fall down, so that supervisor finds the situation of old man timely and can take appropriate measures timely, ensure the safety of old man.
But, the monitoring product of existing human body behavior, generally corresponding pattern is set on product, when wearer uses, need manual intervention, before entering certain behavior, first manually be set to relevant pattern, thus the behavioral data collected under setting behavioral pattern, supervisor also directly can monitor the data under certain behavior of old man, and wearer is generally old man, in use, be easy to forget set model, or, think and use inconvenient and be unwilling to set, thus image data not only can be caused not comprehensive or inaccurate, and the enthusiasm of user can be reduced, the object that its behavior is monitored cannot be reached, and then affect the popularization of product.
Summary of the invention
The object of the present invention is to provide a kind of intelligent terminal based on acceleration information to carry out human body behavior and automatically know method for distinguishing, equipment identifies the behavior of user automatically, and carries out pattern setting without the need to user, thus solves the foregoing problems existed in prior art.
To achieve these goals, the technical solution used in the present invention is as follows:
Intelligent terminal based on acceleration information carries out human body behavior and automatically knows a method for distinguishing, comprises the steps:
S1, obtains the acceleration information of human body behavior;
According to described acceleration information, S2, judges that described human body behavior is erectility or couches state, if couch state, then performs S4; If erectility, then perform S3;
S3, judgement is sitting state or standing state, if sitting state, then performs S7; If standing state, then perform S4;
S4, judgement is resting state or kinestate, if resting state, then performs S7; If kinestate, then make curve movement;
S5, judges described curve movement whether class s ine curve, if not, then perform S7; If so, then the parameter of described curve movement is obtained;
S6, according to the parameter of described curve movement, judges the classification of described kinestate, and performs S7;
S7, judges whether to fall down, and if so, then reports to the police, if not, then enter and circulate next time.
Preferably, described acceleration information is gathered by acceleration transducer.
More preferably, described acceleration transducer is 3-axis acceleration sensor, then the described acceleration in S1 is 3-axis acceleration.
Particularly, the parameter of described curve movement comprises slope, starting point, terminal, frequency, peak value and center line value.
Particularly, S5 is, judge that described class s ine curve is whether regular through center line, if so, then described kinestate is for walking to run; If not, then described kinestate is original place motion.
Particularly, S5 is, judges the number of the peak value of described class s ine curve, if the number of peak value reaches setting value described in continuous print, then described kinestate is for walking to run; Otherwise described kinestate is original place motion.
More specifically, in S5, if described kinestate is for walking to run, then calculating gait parameter, according to the threshold value of described gait parameter and setting, walking to run for running or walking described in determining.
Particularly, described gait parameter, comprises that cadence, step-length, step are wide, pivot angle and leg speed.
Preferably, described circulation is that every 640ms circulates 32 times.
Particularly, judge whether described in S7 to fall down, comprising:
S701, calculates resultant acceleration;
S702, judges that whether described resultant acceleration is lower than threshold values, if so, then performs S703; If not, then enter and circulate next time;
S703, judges whether described and acceleration meets and falls down feature, if met, then fall down, if do not met, then do not fall down.
The invention has the beneficial effects as follows: by the method adopting the embodiment of the present invention to provide, the intelligent terminal gathering old man's behavioral data can be used in, in the process used, without the need to setting behavioral pattern in advance, carry out the collection of old man's behavioral data again, and directly can gather old man's behavioral data, and automatically identify human body behavior, thus solve old man in the process using intelligent terminal, easily forget the problem of set model, make old man be happy to wear and use, and then the data that ensure that collection are accurately, comprehensively, and the applying of intelligent terminal.
Accompanying drawing explanation
Fig. 1 is the method flow schematic diagram that the intelligent terminal based on acceleration information that the embodiment of the present invention provides carries out human body behavior and automatically identifies.
Detailed description of the invention
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with accompanying drawing, the present invention is further elaborated.Should be appreciated that detailed description of the invention described herein only in order to explain the present invention, be not intended to limit the present invention.
The intelligent terminal that the embodiment of the present invention provides can for intelligent terminal conventional in this area, and characteristic and the functions etc. such as its usual method, automatic synchronization, voice broadcast are characteristic and the function of intelligent terminal's routine.
In prior art, when using intelligent terminal to gather old man's behavior, can not automatically identify old man's behavior, automatically can not identify and fall down, under only having wearer first intelligent terminal to be arranged on certain pattern, the old man's behavior under this pattern could be gathered, and in the embodiment of the present invention, provide the method for a kind of automatic identification human body behavior, especially automatically can identify and fall down, do not need any intervention of wearer, therefore, the intelligent terminal of the method using the present embodiment to provide, more meet the feature of user (great majority are old man), thus better realize the healthy object of care old man.
As shown in Figure 1, embodiments provide a kind of intelligent terminal based on acceleration information and carry out human body behavior and automatically know method for distinguishing, comprise the steps:
S1, obtains the acceleration information of human body behavior;
According to described acceleration information, S2, judges that described human body behavior is erectility or couches state, if couch state, then performs S4; If erectility, then perform S3;
S3, judgement is sitting state or standing state, if sitting state, then performs S7; If standing state, then perform S4;
S4, judgement is resting state or kinestate, if resting state, then performs S7; If kinestate, then make curve movement;
S5, judges described curve movement whether class s ine curve, if not, then perform S7; If so, then the parameter of described curve movement is obtained;
S6, according to the parameter of described curve movement, judges the classification of described kinestate, and performs S7;
S7, judges whether to fall down, and if so, then reports to the police, if not, then enter and circulate next time.
Existing smart terminal product, the human body behavior adopting the embodiment of the present invention to provide knows method for distinguishing automatically, smart terminal product can be made for specific user group (being bad to use the old man of mobile phone), without any need for human intervention, just can realize the automatic identification of behavior, and by the data that automatically identify automatically and server sync, by elders wear data upload to server, download consulting, health guidance etc. simultaneously and report content, completely automatically, carry out, do not need smart mobile phone to associate and also do not need any operation of old man.Thus facilitate the use of old man.
In embodiments of the present invention, intelligent terminal can identify the human body behavior collected, but, the behavior that this human body behavior is just put sometime, instead of the continuous print behavior in certain period.By by the human body behavior automatic synchronization of all moment point on server, then can check the human body behavior in one period of continuous time on the server, thus find the human body Behavior law in this continuous time, better behavior monitoring is carried out to user (old man).
In the embodiment of the present invention, on intelligent terminal, the behavior that can identify comprises: couch or uprightly, stand or sitting, static or motion, original place motion or walk run, whether fall down behavior etc.
As will be understood by the skilled person in the art, according to the automatic identifying method of the human body behavior that the embodiment of the present invention provides, human body behavior can also be divided into other classification, and judge that human body behavior can realize according to the common technology means of this area according to acceleration information.
In the embodiment of the present invention, described acceleration information is gathered by acceleration transducer.
In the embodiment of the present invention, described acceleration transducer is 3-axis acceleration sensor, then the described acceleration in S1 is 3-axis acceleration.
As will be understood by the skilled person in the art, the acceleration information that intelligent terminal gathers can also adopt the multi-shaft acceleration transducer outside three axles, obtains multiaxis acceleration information.
In the embodiment of the present invention, judge described human body behavior classification according to described acceleration information, ordinary skill in the art means can be adopted.
In embodiments of the present invention, when judging kinestate, can adopt with the following method:
Production Time point and the curve movement of acceleration information;
Judge whether curve movement is class s ine curve;
If class s ine curve, then find the relevant parameter of done curve movement, wherein, the parameter of described curve movement comprises slope, starting point, terminal, frequency, peak value and center line value.After obtaining the parameter of described curve movement, S5 can be, judge that described class s ine curve is whether regular through center line, if so, then described kinestate is for walking to run; If not, then described kinestate is original place motion.
In the embodiment of the present invention, described regularity through center line, Ke Yiwei: class s ine curve passes twice through center line and represents 1 step, automatically switches to note step mode after monitoring 5 steps continuously, starts note step, and the time window of twice note step is 0.2 to 2s.Be less than or greater than this time window and then exit note step mode.
As will be understood by the skilled person in the art, the regulation that can also be carried out other through center line according to the actual requirements of described regularity; Meanwhile, can also carry out revising or adjusting according to practical situation.
In the embodiment of the present invention, S5 also can be, judges the number of the peak value of described class s ine curve, if the number of peak value reaches setting value described in continuous print, then described kinestate is for walking to run; Otherwise described kinestate is original place motion.
Such as, the number of continuous print peak value reaches 5, then can judge that kinestate is for walking to run, if the number of continuous print peak value does not reach 5, then can judge that kinestate is original place motion.
As will be understood by the skilled person in the art, the setting value of the number of peak value described in described continuous print can also carry out other regulation according to the actual requirements; Meanwhile, can also carry out revising or adjusting according to practical situation.
In the embodiment of the present invention, in S3, describedly then make curve movement if kinestate, also comprise step, calculate quantity of motion, then, in S5, according to the threshold value of described quantity of motion and setting, walk to run for running or walking described in determining.
In the embodiment of the present invention, in S5, if described kinestate is for walking to run, then calculating gait parameter, according to the threshold value of described gait parameter and setting, walking to run for running or walking described in determining.Described gait parameter, comprises that cadence, step-length, step are wide, pivot angle and leg speed.
In the present embodiment, threshold value is by after adding up the agenda data of multiple sample, setting.The such as setting of quantity of motion threshold value, by gathering in multiple real life, the quantity of motion statistics of running behavior, add up with the quantity of motion of walking behavior, drawn the quantity of motion of difference running and walking, namely this difference quantity of motion is used in the behavior differentiation to new sample as threshold value, when quantity of motion is greater than threshold value, then for running, when quantity of motion is less than threshold value, then it is walking.
As will be understood by the skilled person in the art, in practice process, can also constantly revise threshold value, constantly increased by collecting sample quantity, and by the analysis to collecting sample, constantly threshold value is revised, make Human bodys' response more accurate, for follow-up monitoring provides information more accurately.
In the embodiment of the present invention, described circulation is that every 640ms circulates 32 times.
In the embodiment of the present invention, owing to being continual continuous print collection human body behavioral data, so in order to carry out Activity recognition to more data, and ensure that system can be smooth and easy, avoid because program number of run is too much, cause system velocity to decline, or cannot carry out smoothly, adopt every 640ms circulate 32 times mode to gather behavioral data identify.
In the embodiment of the present invention, judge whether described in S7 to fall down, comprising:
S701, calculates resultant acceleration;
S702, judges that whether described resultant acceleration is lower than threshold values, if so, then performs S703; If not, then enter and circulate next time;
S703, judges whether described and acceleration meets and falls down feature, if met, then fall down, if do not met, then do not fall down.
In the embodiment of the present invention, can by multiple sample extraction sign, obtain falling down curve, wherein, vertical coordinate is that the feature of falling down curve of resultant acceleration is comparatively obvious, so can fall down Curves Recognition as the index of falling down by resultant acceleration.In the embodiment of the present invention, when when processing the data of sampling, occur weightlessness, namely resultant acceleration is lower than threshold values, then enter the program identifying and fall down, according to subsequent sampling, judge that the weightlessness persistent period is in threshold values, and occur large impact, the quiescent duration that lies low afterwards is meeting threshold values, then think to meet and fall down feature, be judged as falling down.
At present, the intelligent terminal of falling-resistant is generally gather acceleration information by acceleration transducer, judges whether old man occurs dangerous situations such as falling down according to the calculating gained inclination angle of acceleration information or the change of resultant acceleration value.
But, intelligent terminal's discrimination of the prior art is lower, and in the present invention, by falling down the analysis of data linear character to old man, and through the checking of a large amount of truthful data, the correction of large-scale data test to several threshold points, thus reach the discrimination of 98%.
At present for gathering the terminal of old man's behavioral data, generally gather acceleration information by acceleration transducer, judge that old man remembers the data such as step according to the change of acceleration information, can only after setting behavioral pattern, gather the old man's behavioral data under behavior pattern again, and automatically cannot identify old man's behavior.Therefore old man is needed in the process of terminal, behavioral pattern can only to be set in advance in use.
And, in the embodiment of the present invention, due in the process gathering human body behavior, do not need human intervention, terminal unit can identify human body behavior automatically, so adopt the method that provides of the embodiment of the present invention, intelligent terminal can realize the whole day collection of 24 hours to old man's behavioral data and Activity recognition, thus realize the monitoring of 24 hours of old man's whole day, instead of can only acquisition monitoring to the data in certain behavior period, so, can be more accurate to the judgement of old man's behavior.
By adopting technique scheme disclosed by the invention, obtain effect useful as follows: by the method adopting the embodiment of the present invention to provide, the intelligent terminal gathering old man's behavioral data can be used in, in the process used, without the need to setting behavioral pattern in advance, carry out the collection of old man's behavioral data again, and directly can gather old man's behavioral data, and automatically identify human body behavior, thus solve old man in the process using intelligent terminal, easily forget the problem of set model, old man is made to be happy to wear and use, and then ensure that the data of collection are accurate, comprehensively, and the applying of intelligent terminal.
Each embodiment in this description all adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar part mutually see.
Those skilled in the art it should be understood that the sequential of the method step that above-described embodiment provides can carry out accommodation according to practical situation, also can carry out according to practical situation is concurrent.
The hardware that all or part of step in the method that above-described embodiment relates to can carry out instruction relevant by program has come, described program can be stored in the storage medium that computer equipment can read, for performing all or part of step described in the various embodiments described above method.Described computer equipment, such as: personal computer, server, the network equipment, intelligent mobile terminal, intelligent home device, wearable intelligent equipment, vehicle intelligent equipment etc.; Described storage medium, such as: the storage of RAM, ROM, magnetic disc, tape, CD, flash memory, USB flash disk, portable hard drive, storage card, memory stick, the webserver, network cloud storage etc.
Finally, also it should be noted that, in this article, the such as relational terms of first and second grades and so on is only used for an entity or operation to separate with another entity or operating space, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, commodity or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, commodity or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, commodity or the equipment comprising described key element and also there is other identical element.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications also should look protection scope of the present invention.
Claims (10)
1. carry out human body behavior based on the intelligent terminal of acceleration information and automatically know a method for distinguishing, it is characterized in that, comprise the steps:
S1, obtains the acceleration information of human body behavior;
According to described acceleration information, S2, judges that described human body behavior is erectility or couches state, if couch state, then performs S4; If erectility, then perform S3;
S3, judgement is sitting state or standing state, if sitting state, then performs S7; If standing state, then perform S4;
S4, judgement is resting state or kinestate, if resting state, then performs S7; If kinestate, then make curve movement;
S5, judges described curve movement whether class s ine curve, if not, then perform S7; If so, then the parameter of described curve movement is obtained;
S6, according to the parameter of described curve movement, judges the classification of described kinestate, and performs S7;
S7, judges whether to fall down, and if so, then reports to the police, if not, then enter and circulate next time.
2. the intelligent terminal based on acceleration information according to claim 1 carries out human body behavior and automatically knows method for distinguishing, and it is characterized in that, described acceleration information is gathered by acceleration transducer.
3. the intelligent terminal based on acceleration information according to claim 2 carries out human body behavior and automatically knows method for distinguishing, and it is characterized in that, described acceleration transducer is 3-axis acceleration sensor, then the described acceleration in S1 is 3-axis acceleration.
4. the intelligent terminal based on acceleration information according to claim 1 carries out human body behavior and automatically knows method for distinguishing, and it is characterized in that, the parameter of described curve movement comprises slope, starting point, terminal, frequency, peak value and center line value.
5. the intelligent terminal based on acceleration information according to claim 4 carries out human body behavior and automatically knows method for distinguishing, and it is characterized in that, S5 is, judge described class s ine curve whether regular through center line, if so, then described kinestate is for walking to run; If not, then described kinestate is original place motion.
6. the intelligent terminal based on acceleration information according to claim 4 carries out human body behavior and automatically knows method for distinguishing, it is characterized in that, S5 is, judges the number of the peak value of described class s ine curve, if the number of peak value reaches setting value described in continuous print, then described kinestate is for walking to run; Otherwise described kinestate is original place motion.
7. the intelligent terminal based on acceleration information according to claim 5 or 6 carries out human body behavior and automatically knows method for distinguishing, it is characterized in that, in S5, if described kinestate is for walking to run, then calculate gait parameter, according to the threshold value of described gait parameter and setting, walk to run for running or walking described in determining.
8. the intelligent terminal based on acceleration information according to claim 7 carries out human body behavior and automatically knows method for distinguishing, it is characterized in that, described gait parameter, comprises that cadence, step-length, step are wide, pivot angle and leg speed.
9. the intelligent terminal based on acceleration information according to claim 1 carries out human body behavior and automatically knows method for distinguishing, and it is characterized in that, described circulation is that every 640ms circulates 32 times.
10. the intelligent terminal based on acceleration information according to claim 1 carries out human body behavior and automatically knows method for distinguishing, it is characterized in that, judges whether to fall down, comprising described in S7:
S701, calculates resultant acceleration;
S702, judges that whether described resultant acceleration is lower than threshold values, if so, then performs S703; If not, then enter and circulate next time;
S703, judges whether described and acceleration meets and falls down feature, if met, then fall down, if do not met, then do not fall down.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510020940.1A CN104490401B (en) | 2015-01-15 | 2015-01-15 | Method for intelligent terminal for automatically recognizing human behaviors based on acceleration data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510020940.1A CN104490401B (en) | 2015-01-15 | 2015-01-15 | Method for intelligent terminal for automatically recognizing human behaviors based on acceleration data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104490401A true CN104490401A (en) | 2015-04-08 |
| CN104490401B CN104490401B (en) | 2017-05-24 |
Family
ID=52931929
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510020940.1A Expired - Fee Related CN104490401B (en) | 2015-01-15 | 2015-01-15 | Method for intelligent terminal for automatically recognizing human behaviors based on acceleration data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104490401B (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104841117A (en) * | 2015-05-05 | 2015-08-19 | 惠州Tcl移动通信有限公司 | Counting method and system of sports times based on mobile terminal acceleration sensor |
| CN105212941A (en) * | 2015-08-25 | 2016-01-06 | 武汉理工大学 | A kind of human body active state recognition methods and system |
| CN106295680A (en) * | 2016-07-29 | 2017-01-04 | 深圳云智优泊科技有限公司 | Low-power consumption is driven and ambulatory status identification system |
| CN106598222A (en) * | 2016-11-14 | 2017-04-26 | 上海斐讯数据通信技术有限公司 | Scene mode switching method and system |
| CN107358051A (en) * | 2017-07-18 | 2017-11-17 | 前海随身宝（深圳）科技有限公司 | Motion state of terminal analysis method, mobile terminal and readable storage medium storing program for executing |
| CN108346469A (en) * | 2018-01-15 | 2018-07-31 | 维沃移动通信有限公司 | Method and mobile terminal for determining human health status |
| CN108446019A (en) * | 2018-02-13 | 2018-08-24 | 重庆大学 | A kind of user behavior measurement method and operation correction model based on wearable device sensor technology |
| CN108536158A (en) * | 2017-03-03 | 2018-09-14 | 北京小米移动软件有限公司 | The control method and device of balance car |
| CN109199355A (en) * | 2018-09-18 | 2019-01-15 | 深圳和而泰数据资源与云技术有限公司 | Heart rate information detection method, device and detection device |
| CN109447128A (en) * | 2018-09-29 | 2019-03-08 | 中国科学院自动化研究所 | Walking based on micro- inertial technology and the classification of motions method and system that remains where one is |
| CN110327050A (en) * | 2019-05-05 | 2019-10-15 | 北京理工大学 | People's tumble state embedded intelligence detection method for wearable equipment |
| CN111728327A (en) * | 2019-03-25 | 2020-10-02 | 深圳市贝沃电子科技有限公司 | NB-loT-based old man guarding bracelet |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007160076A (en) * | 2005-11-15 | 2007-06-28 | Univ Nihon | Human posture motion discrimination device and energy consumption calculation device |
| US20090161915A1 (en) * | 2007-12-24 | 2009-06-25 | National Chiao Tung University Of Taiwan | Multi-person pose recognition system using a zigbee wireless sensor network |
| WO2011055255A1 (en) * | 2009-11-03 | 2011-05-12 | Koninklijke Philips Electronics N.V. | Method and system for revoking a fall alarm field of the invention |
| JP2011156099A (en) * | 2010-01-29 | 2011-08-18 | Carecom Co Ltd | Nurse call system |
| CN102302361A (en) * | 2011-06-24 | 2012-01-04 | 东北大学 | Device for monitoring heart rate and physical state |
| CN103006234A (en) * | 2011-09-22 | 2013-04-03 | 惠振宇 | Physical condition monitoring device, safety alert monitoring system and safety alert monitoring method |
| CN103886715A (en) * | 2014-02-28 | 2014-06-25 | 南京邮电大学 | Human body fall detection method |
-
2015
- 2015-01-15 CN CN201510020940.1A patent/CN104490401B/en not_active Expired - Fee Related
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007160076A (en) * | 2005-11-15 | 2007-06-28 | Univ Nihon | Human posture motion discrimination device and energy consumption calculation device |
| US20090161915A1 (en) * | 2007-12-24 | 2009-06-25 | National Chiao Tung University Of Taiwan | Multi-person pose recognition system using a zigbee wireless sensor network |
| WO2011055255A1 (en) * | 2009-11-03 | 2011-05-12 | Koninklijke Philips Electronics N.V. | Method and system for revoking a fall alarm field of the invention |
| JP2011156099A (en) * | 2010-01-29 | 2011-08-18 | Carecom Co Ltd | Nurse call system |
| CN102302361A (en) * | 2011-06-24 | 2012-01-04 | 东北大学 | Device for monitoring heart rate and physical state |
| CN103006234A (en) * | 2011-09-22 | 2013-04-03 | 惠振宇 | Physical condition monitoring device, safety alert monitoring system and safety alert monitoring method |
| CN103886715A (en) * | 2014-02-28 | 2014-06-25 | 南京邮电大学 | Human body fall detection method |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104841117B (en) * | 2015-05-05 | 2017-09-05 | 惠州Tcl移动通信有限公司 | The method of counting and system of times of exercise based on mobile terminal acceleration transducer |
| CN104841117A (en) * | 2015-05-05 | 2015-08-19 | 惠州Tcl移动通信有限公司 | Counting method and system of sports times based on mobile terminal acceleration sensor |
| CN105212941A (en) * | 2015-08-25 | 2016-01-06 | 武汉理工大学 | A kind of human body active state recognition methods and system |
| CN105212941B (en) * | 2015-08-25 | 2017-12-29 | 武汉理工大学 | A kind of human body active state recognition methods and system |
| CN106295680A (en) * | 2016-07-29 | 2017-01-04 | 深圳云智优泊科技有限公司 | Low-power consumption is driven and ambulatory status identification system |
| CN106598222A (en) * | 2016-11-14 | 2017-04-26 | 上海斐讯数据通信技术有限公司 | Scene mode switching method and system |
| CN108536158A (en) * | 2017-03-03 | 2018-09-14 | 北京小米移动软件有限公司 | The control method and device of balance car |
| CN107358051A (en) * | 2017-07-18 | 2017-11-17 | 前海随身宝（深圳）科技有限公司 | Motion state of terminal analysis method, mobile terminal and readable storage medium storing program for executing |
| CN107358051B (en) * | 2017-07-18 | 2018-07-10 | 前海随身宝（深圳）科技有限公司 | Motion state of terminal analysis method, mobile terminal and readable storage medium storing program for executing |
| CN108346469A (en) * | 2018-01-15 | 2018-07-31 | 维沃移动通信有限公司 | Method and mobile terminal for determining human health status |
| CN108446019A (en) * | 2018-02-13 | 2018-08-24 | 重庆大学 | A kind of user behavior measurement method and operation correction model based on wearable device sensor technology |
| CN108446019B (en) * | 2018-02-13 | 2020-11-06 | 重庆大学 | User behavior measurement method based on wearable device sensor technology and operation deviation rectification model |
| CN109199355A (en) * | 2018-09-18 | 2019-01-15 | 深圳和而泰数据资源与云技术有限公司 | Heart rate information detection method, device and detection device |
| CN109199355B (en) * | 2018-09-18 | 2021-09-28 | 深圳和而泰数据资源与云技术有限公司 | Heart rate information detection method and device and detection equipment |
| CN109447128A (en) * | 2018-09-29 | 2019-03-08 | 中国科学院自动化研究所 | Walking based on micro- inertial technology and the classification of motions method and system that remains where one is |
| CN111728327A (en) * | 2019-03-25 | 2020-10-02 | 深圳市贝沃电子科技有限公司 | NB-loT-based old man guarding bracelet |
| CN110327050A (en) * | 2019-05-05 | 2019-10-15 | 北京理工大学 | People's tumble state embedded intelligence detection method for wearable equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104490401B (en) | 2017-05-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104490401A (en) | Method for intelligent terminal for automatically recognizing human behaviors based on acceleration data | |
| CN104539726A (en) | System and method used for concerning behavior rules of the old by children | |
| Riaboff et al. | Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data | |
| CN111208508B (en) | Exercise quantity measuring method, device and electronic equipment | |
| CN107506602A (en) | A kind of big data health forecast system | |
| CN106956271A (en) | Predict the method and robot of affective state | |
| CN104200234A (en) | Human body action modeling and recognizing method | |
| CN115547497B (en) | Myopia prevention and control system and method based on multi-source data | |
| EP3255551A1 (en) | Information processing apparatus, information processing method, and information processing system | |
| CN103691102A (en) | Exercise information monitoring system and method thereof | |
| CN107837087A (en) | A kind of human motion state recognition methods based on smart mobile phone | |
| Yang et al. | Improving the validity of lifelogging physical activity measures in an internet of things environment | |
| CN111063437A (en) | Personalized chronic disease analysis system | |
| CN102246705A (en) | Method and system for analyzing animal behaviours by using signal processing technology | |
| CN105243285A (en) | Big data health forecast system | |
| JP6774579B2 (en) | Walking evaluation system, walking evaluation method, its program, storage medium, mobile terminal, and server | |
| CN110705421A (en) | Body type data processing method and device | |
| CN104519143A (en) | Method and system for improving work and rest health of old people on basis of intelligent terminal | |
| Zhang et al. | Digital twin perception and modeling method for feeding behavior of dairy cows | |
| CN116269220B (en) | Sleep data continuous monitoring and managing method and wearable device | |
| CN108030467A (en) | Electronic bracelet and computer readable storage medium | |
| CN113221776A (en) | Method for identifying general behaviors of ruminant based on artificial intelligence | |
| CN119235275A (en) | Dynamic identification system of motion risk for patients with heart disease | |
| Sengupta et al. | Driver sleep detection: A new and accurate approach | |
| KR102395173B1 (en) | A wearable apparatus to manage health care for companion animal |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170524 Termination date: 20200115 |