CN203931101U - A kind of wearable human paralysis device of falling detection alarm - Google Patents

Abstract

The utility model discloses a kind of wearable human paralysis device of falling detection alarm, described wearable warning device comprises: acceleration transducer, signal processing module, wireless communication module, GPS locating module, human-computer interaction module and alarm module.This device by monitoring human daily behavior whether with human body paralysis backward for matching, and comprehensively judge human body paralysis in conjunction with human-computer interaction module, and give the alarm in time.Its beneficial effect is, volume is little, easy to carry, without any subsidiary sense, meet people's wearing custom, in conjunction with the information fusion of a plurality of acceleration transducer detections, man-machine interaction confirmation, geographic position identification etc., more in conjunction with the sensor of wearing, accuracy is higher, and mass data shows normally to wear loins wearable human paralysis to be fallen to detect and warning device, and accuracy is more than 95%.

Description

A kind of wearable human paralysis device of falling detection alarm

Technical field

The utility model relates generally to a kind of portable wearing equipment that adopts multi-sensor information processing technology, wireless communication technology, is specially a kind of human body paralysis device of falling detection alarm.

Background technology

Along with the development of mechanics of communication and microsensor technology and the continuous progress of information society, make the convenient reliable paralysed warning device again of development become possibility, people wish a kind of device that can automatic alarm while occurring that paralysis falls, to the wounded is given treatment in time.

The difference that paralysis falls and falls: human body may occur that paralysis falls at sitting posture; The process that paralysis falls is often than falling or falling down more slow.

Paralysis could effectively be monitored most of the elderly's daily behavior, has self-learning capability, and everyone daily behavior of energy matched is judged event of the elderly's paralysis thereby reach high-accuracy, and alarm, can greatly reduce mortality ratio.Falling is the inclination of quick moment to be judged more accurate, and cannot accurately judge for falling down slowly or sitting down, as heart attack, substantially can paralysis or the attitude of sitting down weak and limp, and general drop to detection meeting and thought normal behaviour.

Along with Aging Problem is on the rise, for the crowd of over-65s elderly population or inconvenient walking etc., design and a kind ofly dress conveniently, without the human body paralysis of any attached sense, fall to detect and the device of warning, be necessary very much.

There are at present a lot of detection techniques about the aspect of falling, comprise: 1. use acceleration sensing, by analysis acceleration, detect and whether fall, but paralysis does not often possess the very health behavior of sudden change, so can cause in this situation, cannot normally identify, easily erroneous judgement, versatility is poor; 2. by being placed on the pressure transducer of sole, detect, this detection needs user just can identify in the situation of standing, and identification situation is single, and power consumption is large; 3. by video image analysis, the method easily causes the problems such as user's privacy leakage.

Utility model content

For the problems referred to above, the utility model aims to provide the warning device that a kind of human body paralysis based on multisensor falls in pick-up unit, paralysed situation, makes the elderly can obtain the very first time and seek help under paralysis falls state.

For achieving the above object, provide a kind of human body rational in infrastructure, easy to use, that False Rate is low the paralysed device of falling detection alarm.The utility model by the following technical solutions.

A kind of wearable human paralysis device of falling detection alarm, comprise wearable device body, described wearable device body comprise the obliquity sensor at human body angle of inclination, the acceleration transducer that human body is toppled over acceleration, the signal processing module that detection signal is processed, with wireless communication module, GPS locating module, human-computer interaction module and the alarm module of each sensor and extraneous communication.

Described wireless communication module comprises three kinds of functions: from other position wearable device, obtain sensing data, occur that in paralysed situation, sending distress signals obtains help to the contact person who pre-sets and in the time cannot being rescued by SOS.

Wearable device body is located at the waist of human body.

Described human-computer interaction module need to be set user's individual's relevant information, equipment number of wearing and wear position when wearing, and is set in the unexpected rear emergency of appearance center contact method, is provided with button or touch-screen, reaches the object of man-machine interaction.

Described warning device is built-in GPRS communication function also, can send help information to the contact person who sets in advance after there is paralysis.

Described warning device is also built-in with phonetic function or vibration function.

Described warning device, occurring that paralysis falls after identification, for further reducing erroneous judgement, can enter human-computer interaction link, needs wearer to be undertaken by button and equipment corresponding mutual.

Also comprise that zero to a plurality of auxiliary wearable devices, each auxiliary wearable device includes acceleration transducer, wireless communication module.

Described auxiliary wearable device, the accuracy rate that system identification paralysis falls when number is worn in user's increase can improve thereupon.

The position of wearing of described auxiliary wearable device includes but not limited to: the positions such as wrist, ankle, sole, neck; Include but not limited to: any wearable equipment such as intelligent bracelet, Intelligent foot ring, necklace, belt, waistband, shoes, clothes, trousers, cap.

Described auxiliary wearable device, user must at least select the equipment at a position to wear.

Accompanying drawing explanation

Fig. 1 is the different wearing mode diagrams of equipment;

Fig. 2 is hardware device easy structure figure;

Fig. 3 is equipment workflow diagram;

Waist acceleration information figure when Fig. 4 falls for appearance paralysis;

Fig. 5 is the waist acceleration information figure that normal human body is toppled over collection;

Fig. 6 is that system identification is the emergency treatment scheme of paralysis after.

Embodiment

Below in conjunction with the drawings and specific embodiments, the utility model is described in further details.

Fig. 1 is the equipment wearing mode of the present utility model that several classes are different, for simplicity, all discussions are in Fig. 1 the 1st kind of wearing mode and launch below, and other a few class wearing modes have the identical effect that realizes, and it is higher to wear the accuracy rate of the more identifications of utility appliance.

Fig. 2 is the easy structure figure of equipment, comprising: the main equipment that waist is worn and auxiliary wearable device, wherein:

Waist main equipment comprises: signal acquisition module, signal processing module, wireless communication module, GPS locating module, human-computer interaction module and alarm module.

Signal acquisition module has mainly comprised 3 axle acceleration sensors, by I2C, in real time data is delivered to data processing module;

Signal processing module is module most crucial in this equipment, is mainly to receive the data that send from each sensor, and data judges to identification, when being identified as paralysed while falling state, sending the instruction of crying for help and enters emergency flow process;

Wireless communication module is mainly responsible for receiving the sensing data of beaming back from utility appliance;

GPS locating module is mainly while falling state to start working being identified as paralysis, obtains wearer the geographic position of paralysis time occurs;

Human-computer interaction module mainly realize userspersonal information input, the input of equipment wearing mode and, the first emergency contact method and the paralysis validation of information after;

Alarm module is mainly in system identification, to be judged to be paralysis under state, to cry for help, and comprises that send the extremely prior contact person who arranges of distress signals sends distress call simultaneously, strives for obtaining for user the relief of the very first time.

Fig. 3 is the process flow diagram of equipment work.

Step 1.1 is starting outfit first, and equipment carries out initial work;

If step 1.2 is used equipment for the first time, the setting of carrying out userspersonal information comprises: age, sex, height, body weight etc., be stored in the contact method of paralysis after and the information of wearing that equipment is set;

Step 1.3 equipment starts to enter periodic duty state, respectively wears the sensor image data at position and is sent to waist message processing module by wireless communication module and carry out identification decision;

Step 1.4 judges whether current state falls as paralysis;

Step 1.5 enters interactive mode for paralysis when system identification in while falling state, if inquire wearer that you are in good condition, please press acknowledgement key! ", if button is pressed, jump into step 3 continuation execution, otherwise enter step 6;

Step 1.6 enters emergency state, waits for rescue.

System is carried out the paralysed key step of falling to identify:

Step 2.1 initialization, the paralysis slump_sign of falling variable sets to 0, and body gesture indexed variable body_status sets to 0;

Data and waist obliquity data that each acceleration transducer of step 2.2 Real-time Obtaining gathers;

Step 2.3 pair raw data is carried out filtering processing, adopts low pass smothing filtering herein, removes high frequency noise;

Step 2.4, the acceleration information before employing FIFO (queue) pattern storage current point in time in a period of time and corresponding inclination data;

Step 2.5 judges by obtaining the value θ (angle of human body and surface level) of waist obliquity sensor the body gesture that wearer is current, when 60 ° of θ > represent standing state, and when 60 ° of expression tilt states of θ <, when if body gesture becomes tilt state from standing state, add up interval each acceleration transducer of this state variation rate of acceleration change separately, specific practice is:

1) recording body posture becomes the time used_time used that lies low from standing:

When health and horizontal sextant angle θ >=60 °, used_time is 0, when 60 ° of health inclination angle [theta] <, starts timing statistics, until a stationary state timing of 30 ° of health inclination angle [theta] < finishes.

2) add up the acceleration change amount of each acceleration transducer in this process, this sentences waist acceleration transducer is example, and establishing waist acceleration transducer rate of change is waist_change_rate, and account form is:

$\begin{array}{c}\mathrm{waist}\_\mathrm{change}\_\mathrm{rate}\\ =\left(\underset{t=t1}{\overset{t2}{\mathrm{\&Sigma;}}}\underset{i=0}{\overset{3}{\mathrm{\&Sigma;}}}\right|\mathrm{waist}\_{\mathrm{acc}}_i\left(t\right)-\mathrm{waist}\_\mathrm{last}\_{\mathrm{acc}}_i(t-T)\left|\right)\\ /\mathrm{used}\_\mathrm{time}\end{array}$

Waist_acc wherein _i(t) be the t accekeration of i axle constantly; Waist_last_acc _i(t-1) be the t-1 accekeration of i axle constantly; T1 is the zero hour that health is toppled over, and t2 is the cut-off time that health is toppled over, the sampling period that T is acceleration transducer.

Same mode is added up the acceleration change amount of other utility appliance.

If body gesture changes time used_time used, be less than setting threshold TIME_TH (experimental data shows to occur time threshold scope that paralysis falls in 1-5 second), waist rate of acceleration change waist_change_rate is greater than setting threshold CHANGE_TH and waist sensor paralysis is fallen to mark position 1 simultaneously.Experimental data action rate of acceleration change more paralysed fall situation meeting that show to lie down is normally little a lot, and it is relevant that the size of while rate of acceleration change and acceleration transducer sample frequency and acceleration transducer are worn position.

Because the paralysis parts of body of falling situation there will be more consistent acceleration " saltus step " phenomenon, so can strengthen the accuracy that paralysis falls to identify according to the acceleration change of parts of body.Calculate similarly the rate of acceleration change situation of other position acceleration transducers in this time period, if rate of change is greater than setting threshold by the paralysed mark position 1 of corresponding sensor.

As shown in Figure 4, Figure 5, the first width figure is the waist acceleration information while occurring that paralysis falls, and the second width is the waist acceleration information (as: normally lying down) that normal human body is toppled over collection.Therefrom can find out that the acceleration change amplitude of normally toppling over is little and the duration is of a specified duration, and the acceleration change amplitude of paralysis while falling is large and the duration is short.

Step 2.6 statistics paralysis falls the number of probes that zone bit is 1, and calculates paralysis and fall the ratio r of number of probes that zone bit is 1 and total number of probes, if r is in setting threshold scope in, be finally judged to paralysis and fall, the paralysis slump_sign of falling indexed variable is put to 1, enter emergency flow process.

Fig. 6 is emergency processing flow chart.When system current state is identified as paralysis after, enter emergency treatment scheme, the mark position 1 of first crying for help; In order to reduce the False Rate of equipment, will send subsequently voice inquiry and " if yours is in good condition, please press ACK button! ", and repeat to wait for the corresponding of wearer in 20 seconds, if being pressed, acknowledgement key exits flow process, mark position 0, otherwise continue next step emergency; Obtain current wearer's GPS geographical location information, simultaneously for the ease of finding in time wearer, system is converted to relative distance and the azimuth information with respect to address by GPS information according to the GPS information in wearer address, send SOS information to the relatives and friends place setting in advance and seek help, and wait for that the other side is corresponding; If do not obtain the corresponding of the other side in 30 minutes, system enters next step emergency, otherwise exits emergency; Send information to society's emergency reliefs place such as 120,112 and seek relief, and exit emergency flow process.

When human body rest, this normal activity can not exceed acceleration rate threshold, and human body acceleration rate of change is zero, and after 30 minutes, system is closed monitoring automatically, and single-chip microcomputer dormancy, to guarantee battery continuation of the journey.

The above; it is only preferred embodiment of the present utility model; not in order to limit the utility model, any trickle modification that every foundation technical spirit of the present utility model is done above embodiment, be equal to and replace and improve, within all should being included in the protection domain of technical solutions of the utility model.

Claims (5)

1. the wearable human paralysis device of falling detection alarm, it is characterized in that, comprise wearable device body, described wearable device body comprise the obliquity sensor at human body angle of inclination, the acceleration transducer that human body is toppled over acceleration, the signal processing module that detection signal is processed, with wireless communication module, GPS locating module, human-computer interaction module and the alarm module of each sensor and extraneous communication.

2. the wearable human paralysis device of falling detection alarm as claimed in claim 1, is characterized in that, also comprises that zero to a plurality of auxiliary wearable devices, and each auxiliary wearable device includes acceleration transducer, wireless communication module.

3. the wearable human paralysis device of falling detection alarm as claimed in claim 1 or 2, is characterized in that, wearable device body is located at the waist of human body.

4. the wearable human paralysis device of falling detection alarm as claimed in claim 1 or 2, is characterized in that, auxiliary wearable device is located at wrist, ankle, sole or the neck of human body.

5. the wearable human paralysis device of falling detection alarm as claimed in claim 1 or 2, is characterized in that, human-computer interaction module is provided with button or touch-screen.