CN105996990A - Fatigue driving early warning bracelet integrating heart rate and driving action and early warning method - Google Patents
Fatigue driving early warning bracelet integrating heart rate and driving action and early warning method Download PDFInfo
- Publication number
- CN105996990A CN105996990A CN201610279971.3A CN201610279971A CN105996990A CN 105996990 A CN105996990 A CN 105996990A CN 201610279971 A CN201610279971 A CN 201610279971A CN 105996990 A CN105996990 A CN 105996990A
- Authority
- CN
- China
- Prior art keywords
- bracelet
- heart rate
- fatigue driving
- time
- fatigue
- 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.)
- Pending
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording 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, mobility of a limb
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7455—Details of notification to user or communication with user or patient ; user input means characterised by tactile indication, e.g. vibration or electrical stimulation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Public Health (AREA)
- Physics & Mathematics (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Cardiology (AREA)
- Physiology (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
The invention relates to a fatigue driving early warning bracelet integrating a heart rate and a driving action. The bracelet belongs to the technical field of intelligent bracelets and driving auxiliary systems. The bracelet comprises a three-axis acceleration sensor which is embedded in a bracelet shell body, a micro vibration motor, a heart rate sensor which is disposed on the back face of the bracelet, a heart rate sensor module embedded inside the bracelet shell body, a three-axis acceleration sensor module and a micro processor chip. A method comprises the steps that a human body's heart rate is measured, and a real-time heart rate signal is output; action accelerations of a driver's hands in X, Y and Z dimensions are detected, and real-time action acceleration information in the three dimensions is output; and the driver's fatigue driving situation judged comprehensively. If a judgment result shows that the driver stays at a fatigue driving state, the micro vibration motor will be driven to generate vibration, and thus fatigue early warning can be implemented. The bracelet provided by the invention is characterized in that integrated analysis of two types of detected information is carried out, so that the accurate judgment and the early warning can be carried out to the fatigue driving.
Description
Technical field
The invention belongs to Intelligent bracelet and drive assist system technical field, particularly to utilizing this product form of bracelet
Fatigue driving is judged and the method for early warning and technology.
Background technology
Intelligent bracelet is a kind of wearable intelligent electronic device being worn on human body wrist.By built-in various kinds of sensors,
Such as 3-axis acceleration sensor, three-axis gyroscope, GPS (global positioning system), heart rate sensor, temperature sensor, light
Sensor, sensor noise, bio-impedance sensor etc., can to motion conditions such as position, distance, routes, heart rate,
Health status such as skin temperature, and the ambient conditions such as brightness, noise is monitored, it is also possible to realize further sleep monitor,
The functions such as emotion is analyzed, tired prompting.By built-in communication interface, such as bluetooth, Intelligent bracelet can upload the data to
Smart mobile phone, carries out preservation and the process of data by the application program on smart mobile phone.By built-in vibrating motor,
State set in advance can be carried out vibrating alert.Meanwhile, by the button on bracelet and LED etc., letter can be carried out
The setting of single information and display.Typically there is one piece of rechargeable lithium battery in Intelligent bracelet, give internal electronic circuit
Power supply.Intelligent bracelet in early days, major function is used as pedometer, is monitored sleep quality.
During driving a car, there is multiple subjective and objective unsafe factor in people.Such as, in forward travel or reversing
Time, driver, owing to not seeing pedestrian, other vehicles or barrier, causes safe driving accident.And for example, driver by
Driving or uncomfortable in time-out, driving efficiency cannot normally play, and occurs that operation is stagnated or operational error, causes safety to be driven
Sail accident.If additionally, the situation of vehicle itself or condition of road surface are the best, as not enough in tire pressure, emergent roadblock etc., also
Safe driving can be affected.Advanced drive assist system (ADAS), by the rearview mirror of vehicle, lateral telescope, windshield
The sensors such as upper installation photographic head, radar, laser and ultrasound wave, to lane line deviation, front truck collision, pedestrian impact, drive
The fatigue state of the person of sailing is identified and processes, and provides prompting by the mode such as sound, vibration.
At present, domestic and international market there are various Intelligent bracelet and drive assist system product and patent.With phase of the present invention
Product and the patent closed have two classes: a class is the Intelligent bracelet that can detect health state or driver behavior, has
Relate to Analysis of Mental Fatigue and warning;Another kind of is can be that safe driving provides the ADAS product assisted, and have relates to
Analysis of Mental Fatigue and warning.
In recent years, some Intelligent bracelet that health state or driver behavior can be detected are engendered.Enumerate it
In two product and two published patents as follows:
A) Fitbit Charge HR Intelligent bracelet: on the basis of Fitbit Flex product before, the bracelet back side adds
Heart rate sensor, can measure the heart rate of human body, and shows in the display screen enterprising row data of bracelet.
B) 37 degree of healthy bracelets: in addition to motion meter step and sleep are measured, heart rate, respiratory frequency and blood pressure can be measured.
Heart rate can be measured by above-mentioned two Intelligent bracelet product, but without reference to the analysis to fatigue driving.
C) patent " a kind of method and system preventing fatigue driving based on Intelligent bracelet ", Application No. 201410661558.4.
It relate to such a Intelligent bracelet, monitors hand motion, when Intelligent bracelet is quiet by built-in gravity sensor and timer
The most motionless time exceedes certain threshold values, or when the displacement of Intelligent bracelet offset direction dish exceedes certain threshold values, it is judged that
For fatigue driving state, provide warning.
D) patent " a kind of multifunctional portable electronic bracelet ", Application No. 201510626279.9.Which propose such a
Intelligent bracelet framework, by detection devices such as internal pulse wave detector, heart rate detector, detects human parameters, and sends
To controller.Parameter threshold is set in the controller, during superthreshold scope, carries out fatigue driving warning reminding.Meanwhile, by number
According to this and location information is sent to cloud server and carries out data storage, analysis, analyze and easily produce the tired time period.
Above-mentioned two patent is disadvantageous in that, only according to the such single index of heart rate or driver behavior, drives fatigue
Drive into row judgement, easily there is more wrong report phenomenon.Such as, " a kind of fatigue driving is prevented based on Intelligent bracelet in patent
Method and system " in, when driver's waiting signal lamp, driver behavior is stagnated, and now the Intelligent bracelet actionless time surpasses
Cross certain threshold value, fatigue driving will be become by wrong report.Additionally, patent " a kind of multifunctional portable electronic bracelet " is not given
Go out the concrete grammar carrying out fatigue driving analysis based on heart rate information.
In recent years, can be that safe driving provides the ADAS product of auxiliary increasingly to be paid close attention to.Related product and patent are such as
Under:
A) ADAS product based on smart mobile phone: smart mobile phone is placed at the windshield of car by it, utilizes mobile phone camera
As sensor, record the video information of vehicle front.By the ADAS application program in smart mobile phone, to from shooting
The video information of head processes, thus provides the early warning of the situations such as lane line deviation, front truck collision, pedestrian impact.
This series products, mainly by the information of vehicle front is carried out perception and process, provides auxiliary for safe driving, does not relate to
And the analysis of driver tired driving and early warning.
B) patent " a kind of fatigue drive of car prior-warning device ", Application No. 201510949418.1.It discloses a kind of automobile
The framework idea of fatigue driving early-warning device.Intend by photographic head identification driver's facial signal, use bracelet physiological sensing device
Detection driver's hand pulse signal, whether comprehensive descision driver has fatigue driving phenomenon.
This patent is utilized respectively pulse signal and fatigue driving is analyzed by driver's facial signal, and provides early warning, and also
Two kinds of information are not carried out fusion treatment.All can there is wrong report phenomenon in both early warning.Meanwhile, in order to identify driver face
Portion's signal, needs to install on driver opposite photographic head and camera information processing means, implements more complicated.
Summary of the invention
It is contemplated that overcome the deficiency of prior art, design a kind of fatigue driving early warning hands merging heart rate and driver behavior
Ring and method for early warning thereof, physiological feature and the specific driver behavior of driver are detected by the bracelet of the present invention, the present invention
Method two category informations detected are carried out convergence analysis, thus realize accurately judging and early warning of fatigue driving.
A kind of fatigue driving early warning bracelet merging heart rate and driver behavior that the present invention proposes, including being embedded in bracelet housing
3-axis acceleration sensor, vibrating motor and be arranged on the heart rate sensor at the back side of bracelet, it is characterised in that also
Including embedding the interior heart rate sensor module that the signal of heart rate sensor collection is processed of bracelet housing, to 3-axis acceleration
Sensor acquisition signal carries out the 3-axis acceleration sensor module that processes and is previously stored with fatigue driving early warning application program
Microprocessor chip.The heart rate of human body, by sensing the beat pulse of wrist, is measured by heart rate sensor module, defeated
Go out real-time heart rate signal;The hands of driver is added by 3-axis acceleration sensor module in the action of tri-dimensions of X, Y, Z
Speed detects, and exports the action acceleration information of real-time three dimension;Application program in microprocessor chip passes through
Signal from heart rate sensor module and 3-axis acceleration sensor module is acquired and processes, the fatigue to driver
Driving situation carries out comprehensive descision.If by judging, being currently fatigue driving state, then drive vibrating motor, produce
Raw vibration, carries out giving fatigue pre-warning.
The present invention also proposes a kind of method for early warning using above-mentioned early warning bracelet, it is characterised in that the method comprises the following steps:
1) heart rate signal and the collection of 3-axis acceleration information:
1-1) believed by the heart rate of the human pulse of heart rate sensor module Real-time Collection piezoelectric type Micro Energy Lose heart rate sensor detection
Number, export heart rate signal waveform, when new rising edge each in heart rate signal waveform arrives, collect new heart rate signal
After rising edge, forward step 2 to) carry out the analysis of heart rate signal and the judgement of fatigue driving;
1-2) by the detection to driver's hand motion of the 3-axis acceleration sensor module Real-time Collection 3-axis acceleration sensor
Signal, the acceleration information of output tri-dimensions of X, Y, Z, carry out 3-axis acceleration information every the time interval set
Collection, after collecting new 3-axis acceleration information, forward step 3 to) carry out the long-time transfixion of bracelet and bracelet
The judgement jerked;
2) analysis of heart rate signal and the judgement of fatigue driving
After 2-1) collecting new heart rate signal rising edge, first calculate between the time between this rising edge and a upper rising edge
Every, obtain the time interval between twice new heart beating, i.e. phase between RR;The memory buffer of one a length of 100 is set,
For storing the numerical value of phase between nearest 100 RR;
2-2) based on gathering and the heart rate signal of storage, the HRV (heart rate variability) of heart rate signal is analyzed, and
The fatigue state judging driver is analyzed by SDNN (phase standard deviation between RR) index;
The numerical value of SDNN obtains according to the numerical computations of phase between N number of continuous RR:
Wherein RRiIt is the numerical value of phase between i-th RR,It is the average of phase between N continuous RR:
Compare obtaining the SDNN value SDNN threshold value with fatigue driving;If SDNN >=SDNN threshold value, then by tired
Please sail heart rate flag bit flag1 and be set to 1;Otherwise, flag1 is set to 0;
Forward step 4 to), carry out the convergence analysis of fatigue driving;
3) judgement that the long-time transfixion of bracelet and bracelet are jerked:
If the pushing time that steering wheel is held in setting is motionless, or has bigger motion to accelerate in certain direction or multiple directions suddenly
Degree, then it is assumed that be the characteristic action of two kinds of fatigue drivings;
3-1) the calculating of bracelet transfixion cumulative time: by new X, Y, Z axis acceleration information and bracelet transfixion
Acceleration rate threshold compare, if the acceleration of X, Y, Z axis is respectively less than acceleration rate threshold, then it is assumed that three axles accelerate
In degree information gathering time interval, bracelet transfixion, the bracelet transfixion cumulative time is plus 3-axis acceleration information gathering
Time interval;Otherwise, if the acceleration of X, Y, Z axis is all higher than acceleration rate threshold, then the bracelet transfixion cumulative time
Reset;
3-2) actionless judgement long-time to bracelet: by calculated bracelet transfixion cumulative time and bracelet static
Motionless time threshold compares;If bracelet transfixion cumulative time >=time threshold, then it is assumed that the operation of driver
The first fatigue driving characteristic action occurs, fatigue driving timeout flag position flag2 is set to 1;Otherwise, flag2 is set to 0;
3-3) the judgement that bracelet is jerked: calculate the acceleration absolute value sum of X, Y, Z axis, and by it with in advance
The threshold value of the acceleration absolute value sum set compares, if the absolute value sum >=acceleration of the acceleration of X, Y, Z axis
The threshold value of degree absolute value sum, then it is assumed that the second fatigue driving characteristic action occur, exceed the speed limit flag bit flag3 by fatigue driving
It is set to 1, otherwise, then the flag bit flag3 that fatigue driving exceeded the speed limit is set to 0;
Forward step 4 to), carry out the convergence analysis of fatigue driving;
4) convergence analysis to fatigue driving:
According to fatigue driving heart rate flag bit flag1, fatigue driving timeout flag position flag2 and fatigue driving hypervelocity flag bit
The information of flag3, judges fatigue driving, if flag1 and flag2 is 1 simultaneously, or flag1 and flag3 is simultaneously
When 1, it is judged that for fatigue driving, go to step 5);Otherwise, 1 is gone to step);
5) microprocessor chip drives vibrating motor to carry out vibrating early warning;Go to step 1 again).
The feature of the present invention and beneficial effect:
Utilize and in wrist, wear the Intelligent bracelet of the present invention and the method according to the invention carries out fatigue driving early warning, compare and need
The fatigue driving early warning scheme of photographic head and processing means thereof to be installed onboard, simpler easy.The inventive method according to
The information of the sensor within Intelligent bracelet processes and analyzes, and when the fatigue state of driver being detected, drives miniature
Vibrating motor is reminded, and can effectively reduce the security incident caused because of fatigue driving.By to from heart rate sensor
Carry out convergence analysis with the information of 3-axis acceleration sensor, comprehensively carry out tired shape based on heart rate and driver behavior two indices
State is analyzed, and can greatly reduce the wrong report phenomenon using single-sensor information easily to occur when judging.
Accompanying drawing explanation
Fig. 1 is the composition schematic diagram of the Intelligent bracelet of the present invention;
Fig. 2 is the fatigue driving early warning application program Whole Work Flow block diagram of the inventive method;
Fig. 3 is the heart rate signal oscillogram of present invention heart rate sensor based on Intelligent bracelet module output.
Detailed description of the invention
The fusion heart rate of present invention proposition and the fatigue driving early warning bracelet of driver behavior and method for early warning thereof combine accompanying drawing and reality
Execute example and describe in detail as follows:
The main composition of the Intelligent bracelet that the inventive method embodiment uses is as it is shown in figure 1, include: be embedded in the bracelet housing back of the body
The heart rate sensor in face, the piezoelectric type, pressure resistance type or the 3-axis acceleration sensor of condenser type Micro Energy Lose that embed in bracelet housing,
Microprocessor chip and vibrating motor, and also include that embedding the interior signal to heart rate sensor collection of bracelet housing is carried out
The heart rate sensor module processed, gathers, to 3-axis acceleration sensor, the 3-axis acceleration sensor module that signal processes
With the microprocessor chip being previously stored with fatigue driving early warning application program;Heart rate sensor module is by sensing the arteries and veins of wrist
Fight and beat, the heart rate of human body is measured, export real-time heart rate signal;The 3-axis acceleration sensor hands to driver
Action acceleration in tri-dimensions of X, Y, Z detects, and exports the action acceleration information of real-time three dimension;
Application program in microprocessor chip is by from heart rate sensor module and the signal of 3-axis acceleration sensor module
It is acquired and processes, the fatigue driving situation of driver is carried out comprehensive descision.If by judging, currently driven for fatigue
Sail state, then drive vibrating motor, produce vibration, carry out giving fatigue pre-warning.
The heart rate sensor of the present embodiment, 3-axis acceleration sensor, microprocessor chip and vibrating motor all use often
The product of rule bracelet, the process function of the signal processing module of each sensor and the early warning application program of microprocessor chip
Routine techniques all can be used to realize.
A kind of based on above-mentioned early warning bracelet fusion heart rate and the fatigue driving method for early warning of driver behavior that the present invention proposes are real
Executing example, the method Whole Work Flow is as in figure 2 it is shown, comprise the following steps:
1) heart rate signal and the collection of 3-axis acceleration information
The heart rate signal of the human pulse of piezoelectric type Micro Energy Lose heart rate sensor detection 1-1) is gathered by heart rate sensor module,
Output heart rate signal waveform, as shown in Figure 3;Time interval RR between the most every twice heart beatingiIt is referred to as the phase between RR, it
There is fine difference, referred to as heart rate variability (HRV).In the heart rate signal waveform shown in Fig. 3, correspondence is each time
Heart beating all can have a new rising edge.When each new rising edge arrives, after collecting new heart rate signal rising edge,
Forward step 2 to) carry out the analysis of heart rate signal and the judgement of fatigue driving;
1-2) gather 3-axis acceleration sensor by 3-axis acceleration sensor module the detection of driver's hand motion is believed
Number;Output tri-dimensions of X, Y, Z acceleration information, these information in order to identify the specific driver behavior of driver,
The collection of 3-axis acceleration information is carried out every the time interval set.In the inventive method embodiment, every 100ms to three
Axis acceleration information is acquired;After collecting new 3-axis acceleration information, forward step 3 to) to carry out bracelet the most quiet
The judgement that the most motionless and bracelet is jerked.
2) analysis of heart rate signal and the judgement of fatigue driving
After 2-1) collecting new heart rate signal rising edge, first calculate between the time between this rising edge and a upper rising edge
Every, the phase between the newest RR;The memory buffer of one a length of 100 is set, is used for storing between nearest 100 RR the phase
Numerical value;
2-2) based on gathering and the heart rate signal of storage, the heart rate variability of heart rate signal is analyzed, and judges driver
Fatigue state;
(medical research shows, phase standard deviation, i.e. SDNN between the RR in heart rate variability metrics, its numerical value and human body
Fatigue state is relevant.When human body occurs tired, SDNN value significantly increases) the inventive method embodiment passes through SDNN
Index carrys out fatigue analysis driving condition.
The numerical value of SDNN obtains according to the numerical computations of phase between N number of continuous RR:
Wherein RRiIt is the numerical value of phase between i-th RRIt is the average of phase between N continuous RR:
N=100 in the inventive method embodiment.
After being calculated SDNN value, it is compared with the SDNN threshold value of fatigue driving;The inventive method embodiment
Middle this threshold value is set to 50ms.More reasonably fatigue driving SDNN threshold value, can be demarcated by experiment, so
Routine techniques is utilized to be configured by smart mobile phone afterwards.If SDNN >=50ms, then by fatigue driving heart rate flag bit flag1
It is set to 1;Otherwise, flag1 is set to 0;
After the analysis of heart rate signal and the judgement step of fatigue driving complete, forward step 4 to), the fusion carrying out fatigue driving divides
Analysis;
3) judgement that the long-time transfixion of bracelet and bracelet are jerked:
Learn that people, when normal driving, if keeping straight on, holds the hands of steering wheel clockwise, the most alternately according to general knowledge
Carry out the motion of little scope;If turning left, (right) turns round, and the hands holding steering wheel moves the most continuously, the most clockwise
The motion in direction, counterclockwise the least scope.
In the inventive method embodiment, if the pushing time that steering wheel is held in setting is motionless, or suddenly in certain direction or multiple
There is bigger acceleration of motion in direction, then it is assumed that be the characteristic action of two kinds of typical fatigue drivings.
After collecting new 3-axis acceleration information, both fatigue drivings that bracelet transfixion and bracelet are jerked
Characteristic action judges.
3-1) as in figure 2 it is shown, first carry out the calculating of bracelet transfixion cumulative time.New X, Y, Z axis is accelerated
Degree information acceleration rate threshold actionless with bracelet compares, and this threshold value is set in the inventive method embodiment
0.1m/s2.If the acceleration of X, Y, Z axis is respectively less than threshold value 0.1m/s2, then it is assumed that in the 3-axis acceleration information gathering time
In interval, bracelet transfixion, the bracelet transfixion cumulative time is plus 3-axis acceleration information gathering time interval 100ms;
Otherwise, if the acceleration of X, Y, Z axis is all higher than threshold value 0.1m/s2, then the bracelet transfixion cumulative time resets;
3-2) actionless judgement long-time to bracelet: by calculated bracelet transfixion cumulative time and bracelet static
Motionless time threshold compares.This threshold value is set to 2s by the inventive method embodiment.If bracelet transfixion is tired out
Between timing >=2s, then it is assumed that stagnating occurs in the operation of driver, and the first fatigue driving in the inventive method embodiment occurs
Characteristic action, is set to 1 by fatigue driving timeout flag position flag2;Otherwise, flag2 is set to 0;
3-3) as in figure 2 it is shown, carry out the judgement that bracelet is jerked the most again.The acceleration calculating X, Y, Z axis is absolute
Value sum, and it and threshold value set in advance are compared.This threshold value is set to 6m/s by the inventive method embodiment2。
If the absolute value sum >=6m/s of the acceleration of X, Y, Z axis2, then it is assumed that the second in the inventive method embodiment occurs
, i.e. there is unexpected driver behavior in fatigue driving characteristic action on certain direction or multiple directions, by fatigue driving hypervelocity mark
Will position flag3 is set to 1.Otherwise, if the absolute value sum < 6m/s of the acceleration of X, Y, Z axis2, then fatigue driving is surpassed
Speed flag bit flag3 is set to 0.
More reasonably bracelet transfixion acceleration rate threshold, bracelet transfixion time threshold and 3-axis acceleration absolute value sum
Threshold value, can be demarcated by experiment, then utilize routine techniques to be configured by smart mobile phone.
After the judgement step that the long-time transfixion of bracelet and bracelet are jerked completes, forward step 4 to), carry out fatigue driving
Convergence analysis.
4) convergence analysis to fatigue driving:
This step is to step 2) obtain fatigue driving judged result, step 3 by heart rate signal analysis) accelerated by three axles
The long-time transfixion of bracelet that degree information obtains and result of jerking carry out convergence analysis, thus judge whether driver locates
In fatigue driving state.
In this step, drive according to fatigue driving heart rate flag bit flag1, fatigue driving timeout flag position flag2 and fatigue
Sail the information of hypervelocity flag bit flag3, fatigue driving is judged.If flag1 and flag2 is 1, or flag1 simultaneously
When being 1 with flag3, it is judged that for fatigue driving, go to step 5) simultaneously;Otherwise, 1 is gone to step);
5) when step 4) judge when driver is in fatigue driving state, microprocessor chip drives vibrating motor to carry out
Vibration early warning;
After the convergence analysis of fatigue driving and vibration warning step complete, return again to step 1), carry out heart rate signal and three axles
The collection of acceleration information.
Claims (2)
1. merge a fatigue driving early warning bracelet for heart rate and driver behavior, add including three axles being embedded in bracelet housing
The heart rate sensor at velocity sensor, vibrating motor and the back side being arranged on bracelet, it is characterised in that also include embedding
The heart rate sensor module in bracelet housing processed the signal of heart rate sensor collection, adopts 3-axis acceleration sensor
Collection signal carries out the 3-axis acceleration sensor module processed and the micro-process being previously stored with fatigue driving early warning application program
Device chip.The heart rate of human body, by sensing the beat pulse of wrist, is measured, exports real-time by heart rate sensor module
Heart rate signal;The hands of driver is carried out by 3-axis acceleration sensor module at the action acceleration of tri-dimensions of X, Y, Z
Detection, exports the action acceleration information of real-time three dimension;Application program in microprocessor chip is by from the heart
The signal of rate sensor assembly and 3-axis acceleration sensor module is acquired and processes, the fatigue driving situation to driver
Carry out comprehensive descision.If by judging, being currently fatigue driving state, then driving vibrating motor, producing vibration,
Carry out giving fatigue pre-warning.
2. the method for early warning using early warning bracelet as claimed in claim 1, it is characterised in that the method includes following
Step:
1) heart rate signal and the collection of 3-axis acceleration information:
1-1) believed by the heart rate of the human pulse of heart rate sensor module Real-time Collection piezoelectric type Micro Energy Lose heart rate sensor detection
Number, export heart rate signal waveform, when new rising edge each in heart rate signal waveform arrives, collect new heart rate signal
After rising edge, forward step 2 to) carry out the analysis of heart rate signal and the judgement of fatigue driving;
1-2) by the detection to driver's hand motion of the 3-axis acceleration sensor module Real-time Collection 3-axis acceleration sensor
Signal, the acceleration information of output tri-dimensions of X, Y, Z, carry out 3-axis acceleration information every the time interval set
Collection, after collecting new 3-axis acceleration information, forward step 3 to) carry out the long-time transfixion of bracelet and bracelet
The judgement jerked;
2) analysis of heart rate signal and the judgement of fatigue driving
After 2-1) collecting new heart rate signal rising edge, first calculate between the time between this rising edge and a upper rising edge
Every, obtain the time interval between twice new heart beating, i.e. phase between RR;The memory buffer of one a length of 100 is set,
For storing the numerical value of phase between nearest 100 RR;
2-2) based on gathering and the heart rate signal of storage, heart rate variability HRV of heart rate signal is analyzed, and passes through
Between RR, standard deviation SDNN index analyzes the fatigue state judging driver the phase;
The numerical value of SDNN obtains according to the numerical computations of phase between N number of continuous RR:
Wherein RRiIt is the numerical value of phase between i-th RR,It is the average of phase between N continuous RR:
Compare obtaining the SDNN value SDNN threshold value with fatigue driving;If SDNN >=SDNN threshold value, then by tired
Please sail heart rate flag bit flag1 and be set to 1;Otherwise, flag1 is set to 0;
Forward step 4 to), carry out the convergence analysis of fatigue driving;
3) judgement that the long-time transfixion of bracelet and bracelet are jerked:
If the pushing time that steering wheel is held in setting is motionless, or has bigger motion to accelerate in certain direction or multiple directions suddenly
Degree, then it is assumed that be the characteristic action of two kinds of fatigue drivings;
3-1) the calculating of bracelet transfixion cumulative time: by new X, Y, Z axis acceleration information and bracelet transfixion
Acceleration rate threshold compare, if the acceleration of X, Y, Z axis is respectively less than acceleration rate threshold, then it is assumed that three axles accelerate
In degree information gathering time interval, bracelet transfixion, the bracelet transfixion cumulative time is plus 3-axis acceleration information gathering
Time interval;Otherwise, if the acceleration of X, Y, Z axis is all higher than acceleration rate threshold, then the bracelet transfixion cumulative time
Reset;
3-2) actionless judgement long-time to bracelet: by calculated bracelet transfixion cumulative time and bracelet static
Motionless time threshold compares;If bracelet transfixion cumulative time >=time threshold, then it is assumed that the operation of driver
The first fatigue driving characteristic action occurs, fatigue driving timeout flag position flag2 is set to 1;Otherwise, flag2 is set to 0;
3-3) the judgement that bracelet is jerked: calculate the acceleration absolute value sum of X, Y, Z axis, and by it with in advance
The threshold value of the acceleration absolute value sum set compares, if the absolute value sum >=acceleration of the acceleration of X, Y, Z axis
The threshold value of degree absolute value sum, then it is assumed that the second fatigue driving characteristic action occur, exceed the speed limit flag bit flag3 by fatigue driving
It is set to 1, otherwise, then the flag bit flag3 that fatigue driving exceeded the speed limit is set to 0;
Forward step 4 to), carry out the convergence analysis of fatigue driving;
4) convergence analysis to fatigue driving:
According to fatigue driving heart rate flag bit flag1, fatigue driving timeout flag position flag2 and fatigue driving hypervelocity flag bit
The information of flag3, judges fatigue driving, if flag1 and flag2 is 1 simultaneously, or flag1 and flag3 is simultaneously
When 1, it is judged that for fatigue driving, go to step 5);Otherwise, 1 is gone to step);
5) microprocessor chip drives vibrating motor to carry out vibrating early warning;Go to step 1 again).
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610279971.3A CN105996990A (en) | 2016-04-29 | 2016-04-29 | Fatigue driving early warning bracelet integrating heart rate and driving action and early warning method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610279971.3A CN105996990A (en) | 2016-04-29 | 2016-04-29 | Fatigue driving early warning bracelet integrating heart rate and driving action and early warning method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN105996990A true CN105996990A (en) | 2016-10-12 |
Family
ID=57081990
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610279971.3A Pending CN105996990A (en) | 2016-04-29 | 2016-04-29 | Fatigue driving early warning bracelet integrating heart rate and driving action and early warning method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN105996990A (en) |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106361308A (en) * | 2016-11-08 | 2017-02-01 | 京东方科技集团股份有限公司 | Method and system for detecting abnormal state |
CN106448061A (en) * | 2016-11-01 | 2017-02-22 | 合肥洛维信息科技有限公司 | Monitoring system for fatigue driving of driver |
CN108146344A (en) * | 2018-01-05 | 2018-06-12 | 吉林大学 | A kind of driver fatigue monitor system based on Multi-source Information Fusion |
CN108665680A (en) * | 2018-05-10 | 2018-10-16 | 武汉理工大学 | A kind of turnpike driving people's fatigue monitoring early warning system based on Intelligent bracelet |
CN108711204A (en) * | 2018-05-18 | 2018-10-26 | 长安大学 | A kind of the driving abnormality detection system and method for comprehensive people-Che-road multi-source information |
CN109224294A (en) * | 2018-09-05 | 2019-01-18 | 深圳曼瑞德科技有限公司 | A kind of fatigue monitoring and preventing mean |
CN109421732A (en) * | 2017-08-16 | 2019-03-05 | 深圳如探索科技有限公司 | Apparatus control method and device |
CN109549297A (en) * | 2018-11-30 | 2019-04-02 | 努比亚技术有限公司 | Assisting automobile driver method, Intelligent bracelet and storage medium based on Intelligent bracelet |
CN109846459A (en) * | 2019-01-18 | 2019-06-07 | 长安大学 | A kind of fatigue driving state monitoring method |
CN109993119A (en) * | 2019-03-31 | 2019-07-09 | 广东乐之康医疗技术有限公司 | A kind of data collection and learning method based on wearable device |
CN110648501A (en) * | 2019-09-26 | 2020-01-03 | 泽一交通工程咨询(上海)有限公司 | Driving fatigue monitoring and alarming device based on video and bracelet and operation method thereof |
CN113538912A (en) * | 2021-07-16 | 2021-10-22 | 金茂智慧科技(广州)有限公司 | Communication control method and related device |
CN117612334A (en) * | 2023-12-14 | 2024-02-27 | 鱼快创领智能科技(南京)有限公司 | Driving safety reminding system and method based on intelligent watch |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103021134A (en) * | 2012-12-10 | 2013-04-03 | 郭文浩 | Monitoring and alarm device for fatigue driving of automobile |
CN203102530U (en) * | 2012-12-03 | 2013-07-31 | 长安大学 | Bus driver fatigue early-warning apparatus |
CN103714660A (en) * | 2013-12-26 | 2014-04-09 | 苏州清研微视电子科技有限公司 | System for achieving fatigue driving judgment on basis of image processing and fusion between heart rate characteristic and expression characteristic |
CN103824420A (en) * | 2013-12-26 | 2014-05-28 | 苏州清研微视电子科技有限公司 | Fatigue driving identification system based on heart rate variability non-contact measuring |
CN103956028A (en) * | 2014-04-23 | 2014-07-30 | 山东大学 | Automobile multielement driving safety protection method |
CN104825174A (en) * | 2015-04-17 | 2015-08-12 | 深圳市元征科技股份有限公司 | Fatigue state detection method and terminal |
CN105243789A (en) * | 2015-08-31 | 2016-01-13 | 江苏智海电子技术有限公司 | Fatigue driving detection method of fusing electrocardiosignal and steering wheel holding pressure |
US20160071393A1 (en) * | 2014-09-09 | 2016-03-10 | Torvec, Inc. | Systems, methods, and apparatus for monitoring alertness of an individual utilizing a wearable device and providing notification |
-
2016
- 2016-04-29 CN CN201610279971.3A patent/CN105996990A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN203102530U (en) * | 2012-12-03 | 2013-07-31 | 长安大学 | Bus driver fatigue early-warning apparatus |
CN103021134A (en) * | 2012-12-10 | 2013-04-03 | 郭文浩 | Monitoring and alarm device for fatigue driving of automobile |
CN103714660A (en) * | 2013-12-26 | 2014-04-09 | 苏州清研微视电子科技有限公司 | System for achieving fatigue driving judgment on basis of image processing and fusion between heart rate characteristic and expression characteristic |
CN103824420A (en) * | 2013-12-26 | 2014-05-28 | 苏州清研微视电子科技有限公司 | Fatigue driving identification system based on heart rate variability non-contact measuring |
CN103956028A (en) * | 2014-04-23 | 2014-07-30 | 山东大学 | Automobile multielement driving safety protection method |
US20160071393A1 (en) * | 2014-09-09 | 2016-03-10 | Torvec, Inc. | Systems, methods, and apparatus for monitoring alertness of an individual utilizing a wearable device and providing notification |
CN104825174A (en) * | 2015-04-17 | 2015-08-12 | 深圳市元征科技股份有限公司 | Fatigue state detection method and terminal |
CN105243789A (en) * | 2015-08-31 | 2016-01-13 | 江苏智海电子技术有限公司 | Fatigue driving detection method of fusing electrocardiosignal and steering wheel holding pressure |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106448061A (en) * | 2016-11-01 | 2017-02-22 | 合肥洛维信息科技有限公司 | Monitoring system for fatigue driving of driver |
CN106361308A (en) * | 2016-11-08 | 2017-02-01 | 京东方科技集团股份有限公司 | Method and system for detecting abnormal state |
CN109421732A (en) * | 2017-08-16 | 2019-03-05 | 深圳如探索科技有限公司 | Apparatus control method and device |
CN108146344A (en) * | 2018-01-05 | 2018-06-12 | 吉林大学 | A kind of driver fatigue monitor system based on Multi-source Information Fusion |
CN108665680A (en) * | 2018-05-10 | 2018-10-16 | 武汉理工大学 | A kind of turnpike driving people's fatigue monitoring early warning system based on Intelligent bracelet |
CN108711204A (en) * | 2018-05-18 | 2018-10-26 | 长安大学 | A kind of the driving abnormality detection system and method for comprehensive people-Che-road multi-source information |
CN109224294A (en) * | 2018-09-05 | 2019-01-18 | 深圳曼瑞德科技有限公司 | A kind of fatigue monitoring and preventing mean |
CN109549297A (en) * | 2018-11-30 | 2019-04-02 | 努比亚技术有限公司 | Assisting automobile driver method, Intelligent bracelet and storage medium based on Intelligent bracelet |
CN109846459A (en) * | 2019-01-18 | 2019-06-07 | 长安大学 | A kind of fatigue driving state monitoring method |
CN109993119A (en) * | 2019-03-31 | 2019-07-09 | 广东乐之康医疗技术有限公司 | A kind of data collection and learning method based on wearable device |
CN110648501A (en) * | 2019-09-26 | 2020-01-03 | 泽一交通工程咨询(上海)有限公司 | Driving fatigue monitoring and alarming device based on video and bracelet and operation method thereof |
CN113538912A (en) * | 2021-07-16 | 2021-10-22 | 金茂智慧科技(广州)有限公司 | Communication control method and related device |
CN117612334A (en) * | 2023-12-14 | 2024-02-27 | 鱼快创领智能科技(南京)有限公司 | Driving safety reminding system and method based on intelligent watch |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105996990A (en) | Fatigue driving early warning bracelet integrating heart rate and driving action and early warning method | |
US10640122B2 (en) | Driving consciousness estimation device | |
US10759438B2 (en) | System and method for responding to driver state | |
CN111166357A (en) | Fatigue monitoring device system with multi-sensor fusion and monitoring method thereof | |
EP4175860B1 (en) | Motion sickness detection system for autonomous vehicles | |
CN107200022B (en) | Driving assistance system and method | |
CN104794855B (en) | Driver attention's comprehensive evaluating device | |
Lee et al. | Wristband-type driver vigilance monitoring system using smartwatch | |
CN103927848A (en) | Safe driving assisting system based on biological recognition technology | |
CN108563891B (en) | Intelligent traffic accident prevention method based on inertial measurement unit | |
CN103956028A (en) | Automobile multielement driving safety protection method | |
JP2019195377A (en) | Data processing device, monitoring system, awakening system, data processing method, and data processing program | |
CN108186034B (en) | Driver fatigue detection device and working method | |
Wei et al. | Multi-source information fusion for drowsy driving detection based on wireless sensor networks | |
TW201441080A (en) | Fatigue driving monitoring system and method | |
CN112455461B (en) | Human-vehicle interaction method for automatically driving vehicle and automatically driving system | |
Arunasalam et al. | Real-time drowsiness detection system for driver monitoring | |
CN205405809U (en) | Driver fatigue detection alarm system based on intelligence wrist -watch | |
CN113012394A (en) | Fatigue driving early warning system and method integrating heart rate and steering wheel action characteristics | |
CN110329405A (en) | One kind is ridden management system | |
JP2019195376A (en) | Data processing device, monitoring system, awakening system, data processing method, and data processing program | |
CN206421551U (en) | A kind of safety assisting system of preventing fatigue driving | |
CN210337901U (en) | Intelligent automobile seat | |
CN108100018A (en) | A kind of intelligent steering wheel with somatic data monitoring and fingerprint identification function | |
TWM512526U (en) | Fatigue driving monitoring device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20161012 |
|
WD01 | Invention patent application deemed withdrawn after publication |