CN113057605A - Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof - Google Patents

Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof Download PDF

Info

Publication number
CN113057605A
CN113057605A CN202110213567.7A CN202110213567A CN113057605A CN 113057605 A CN113057605 A CN 113057605A CN 202110213567 A CN202110213567 A CN 202110213567A CN 113057605 A CN113057605 A CN 113057605A
Authority
CN
China
Prior art keywords
driving
driver
intelligent
cloud platform
heart rate
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
Application number
CN202110213567.7A
Other languages
Chinese (zh)
Inventor
周长阳
殷军伟
邹东平
宋茜
管涛
管建国
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sansan Intelligent Technology Suzhou Co ltd
Sansan Intelligent Technology Rizhao Co ltd
Original Assignee
Sansan Intelligent Technology Suzhou Co ltd
Sansan Intelligent Technology Rizhao Co ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Sansan Intelligent Technology Suzhou Co ltd, Sansan Intelligent Technology Rizhao Co ltd filed Critical Sansan Intelligent Technology Suzhou Co ltd
Priority to CN202110213567.7A priority Critical patent/CN113057605A/en
Publication of CN113057605A publication Critical patent/CN113057605A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/64—Back-rests or cushions
    • 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
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • 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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/90—Details or parts not otherwise provided for
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2503/00—Evaluating a particular growth phase or type of persons or animals
    • A61B2503/20—Workers
    • A61B2503/22—Motor vehicles operators, e.g. drivers, pilots, captains

Abstract

The invention relates to the technical field of health index monitoring, in particular to a personnel heart rate and respiratory rate dynamic monitoring system based on an intelligent seat backrest and a data processing method thereof. The intelligent seat backrest comprises a backrest framework and a cover sleeve, and the flexible sensor and the data transmission device are fixed between the backrest framework and the cover sleeve and are connected with the data transmission device; the data transmission device is connected with the cloud platform, the terminal and the intelligent vehicle system, and based on the dynamic health index monitoring system of the intelligent seat backrest and the data processing method thereof, the system for monitoring the body health index of the driver is combined with the intelligent seat backrest, so that the functions of actively monitoring the physical signs of the driver, reminding and warning fatigue driving and body abnormity and analyzing the driving habits are realized. Long-term data acquisition and analysis can form health and driving habit files of drivers, discover physical abnormality in time, prejudge potential diseases, reduce the risk of disease outburst, correct driving habits and drive safely and civilized.

Description

Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof
Technical Field
The invention relates to the technical field of health index monitoring, in particular to a personnel heart rate and respiratory rate dynamic monitoring system based on an intelligent seat backrest and a data processing method thereof.
Background
With the development of science and technology and the social progress, the rhythm of human life is faster and faster, and the health problem is increasingly highlighted. People are concerned about their health status more and more, and when we drive vehicles alone, the outburst of some potential diseases can bring great influence, and fatigue driving and bad driving are easy to cause traffic accidents to cause losses.
Before fatigue driving or potential diseases occur, the heart rate and the respiratory rate of the driver are predicted, so that the dynamic monitoring of physical indexes of the driver is very important for preventing fatigue driving, sudden diseases and the like. Most of the existing personal sign monitoring devices are intelligent wearable devices, and comprehensive monitoring on the trip state cannot be provided in a targeted manner.
Data acquisition point is single to intelligence dress, need dress in advance and charge, uses inconveniently, does not have the mobile unit that can initiatively provide the monitoring on the vehicle yet, and the seat back closely related with the driver only can provide the supporting role for the driver, lacks intelligent.
Disclosure of Invention
The invention provides a health index dynamic monitoring system based on an intelligent seat backrest, which aims to achieve the purposes of monitoring the heart rate and the respiratory rate of a driver, judging the body state and the driving posture of the driver, giving a prompt in time, or connecting an intelligent system of a vehicle to take emergency response measures and avoiding accidents through matrix data acquisition.
An intelligent seat back, its characterized in that: the flexible sensor is one or the combination of two or more of a polymer piezoelectric sensor, a polymer piezoresistive sensor or an inorganic ceramic material pressure sensor; the flexible sensor is connected with the data transmission device by using a shielding lead; the data transmission device comprises an amplifying circuit, a data analysis module and a wireless network module, wherein the amplifying circuit, the data analysis module and the wireless network module of the data transmission device are respectively connected with a power supply module, and the power supply module is powered by a lithium battery or an external power supply.
Furthermore, the flexible sensors are distributed on the backrest in a matrix manner.
Further, the number of flexible sensors is at least 3 rows and 3 columns.
Further, the flexible sensor is of a SS-S001 model.
Furthermore, the flexible sensor is connected with an amplifying circuit of the data transmission device through an independent shielding lead.
Further, the data analysis module of the data transmission device adopts an STM32 processor.
The utility model provides a health index dynamic monitoring system based on intelligence backrest which characterized in that: the intelligent seat comprises a flexible sensor and a data transmission device of an intelligent seat backrest, a cloud platform, a vehicle intelligent system and a terminal; the cloud platform is connected with a wireless network module and a terminal of the data transmission device in a wireless mode; the intelligent system of the vehicle is connected with the wireless network module of the data transmission device in a wired or wireless mode; the wireless mode is WIFI or an intelligent vehicle networking system network; the terminal is any one of a vehicle-mounted large screen, a mobile phone, a PAD and a computer.
A data processing method of a health index dynamic monitoring system based on an intelligent seat backrest is characterized by comprising the following steps:
the method comprises the following steps: a flexible sensor of the intelligent seat backrest collects signals formed by the body fitting pressure of a driver, and the signals are transmitted to a data analysis module through an amplifying circuit;
step two: the data analysis module counts signals continuously transmitted by the same sensor within a period of time, compares the statistical data of all flexible sensors, takes the signals with the variation amplitude within a set range as stable signals, determines the flexible sensors as main sensors for monitoring the heart rate and the respiratory rate of a driver, performs preliminary analysis and filtration on the amplified signals of the main sensors, and removes interference signals;
step three: the data without interference is sent to a cloud platform through a wireless network module, the cloud platform analyzes the signals through a signal processing algorithm, the breathing rate and the heart rate are separated and identified, and the body state of the driver is judged according to the identified values of the heart rate and the breathing rate; setting the heart rate at 60-100 times/min and the respiration at 16-20 times/min according to the corresponding heart rate and respiration rate in different physical states, wherein the heart rate and the respiration rate are regular states; the heart rate is more than 100 times/min, the respiration is more than 20 times/min, and the heart rate and the respiration are regularly in a fatigue driving state; the heart rate is at 100-;
step four: the cloud platform sends the heart rate and respiratory rate data of the driver to the terminal; when a driver is in a fatigue driving state or an atrial fibrillation state, the cloud platform sends voice reminding or warning to the terminal; or the cloud platform sends the voice reminding or warning signal to the intelligent vehicle system through the wireless network module, and performs voice broadcast and takes corresponding measures according to the control setting of the intelligent vehicle system on the loudspeaker, the brake and the lighting system;
step five: the data analysis module counts the working time of the flexible sensor, if the working time exceeds 3.5 hours and the driving is judged to be fatigue, the information is sent to the cloud platform, the cloud platform transmits warning information to the terminal or the intelligent vehicle system, and the terminal or the intelligent vehicle system sends out voice reminding or warning;
step six: data such as the heart rate of a driver are counted and analyzed for a long time, and health reports are pushed to a terminal every week, so that the driver can know the physical state of the driver and can make a prejudgment on potential diseases;
step seven: the data analysis module counts the voltage of the signal measured by each flexible sensor within a period of time, takes the time period of the signal variation amplitude of each flexible sensor within a set range as a reference time period, and takes the voltage average value P of each flexible sensor in the time period as a reference value for judging the driving habit; taking an average value P' of voltage values of all the flexible sensors in a certain time period when the signals fluctuate as a comparison value for judging the driving habits;
step eight: in the driving process, when all P 'is reduced relative to a reference value, the data analysis module judges that sudden braking or braking occurs, the maximum value of all sensors | P' -P | is taken, when | P '-P | is more than or equal to a threshold I, the sudden braking occurs, and the threshold II < | P' -P | < the threshold I is normal braking; when all P ' is increased, judging that quick refueling or refueling is carried out, when P ' -P is more than or equal to a threshold I, carrying out quick refueling, and when the threshold II < | P ' -P | < the threshold I, carrying out refueling;
step nine: in the driving process, relative to a reference value, the left row of flexible sensors P 'is increased, the right row of flexible sensors P' is decreased, the data analysis module judges that the vehicle turns left, and otherwise, the vehicle turns right; taking the maximum value of all sensors | P ' -P |, wherein when | P ' -P | > is more than or equal to a threshold I, the sensor is in sharp turning, and a threshold II < | P ' -P | < threshold I is in normal turning;
step ten: in the driving process, compared with a reference value, the row and column signal contrast value sensed by the flexible sensor matrix is increased or reduced to be unbalanced, and the data analysis module judges that the sitting posture of a driver is abnormal;
step eleven: the data analysis module transmits driving behavior information in the driving process to the cloud platform through the wireless network module, the cloud platform transmits the driving behavior in the driving process to the terminal and carries out voice reminding on improper driving behaviors, or the cloud platform transmits the driving behavior to the intelligent system of the vehicle through the wireless network module and carries out voice reminding on improper driving behaviors through a loudspeaker; and the cloud end platform collects and counts the driving behavior in the driving process, analyzes the driving habit of the driver through an algorithm and transmits the driving habit to the terminal.
According to the intelligent seat backrest-based health index dynamic monitoring system and the data processing method thereof, the matrix type flexible sensor is fixed between the backrest framework and the backrest cover, the heart rate and respiratory rate data of a driver are collected at multiple points, and the data accuracy is improved. Through long-term data analysis, establish driver health archives, in time discover driver's health unusual and pronunciation warning remind or intelligent system take corresponding measure, effectively prevent driver fatigue driving and latent disease, avoid unexpected emergence, analysis driver driving habit forms driving habit report, helps correcting the bad habit of driving, safe driving.
Drawings
The accompanying drawings disclose, in part, specific embodiments of the present invention, wherein,
FIG. 1 is a schematic view of the connection of a flexible sensor and a data transmission device according to the present invention;
FIG. 2 is a schematic diagram of a matrix distribution of flexible sensors according to the present invention;
fig. 3 is a schematic view of the working process of the dynamic health index monitoring system for the intelligent automobile-based seat back of the invention.
Detailed Description
As shown in fig. 1 to 3, the intelligent seat back provided by the invention comprises a back frame, a back cover sleeve 1 is sleeved on the back frame, a flexible sensor 3 and a data transmission device 2 are fixed between the back frame and the back cover sleeve 1, the flexible sensor 3 is a SS-S001 type polymer piezoelectric sensor, and the back is distributed in 3 rows and 3 columns of matrix type; the data transmission device 2 comprises an amplifying circuit, a data analysis module and a wireless network module, the amplifying circuit, the data analysis module and the wireless network module of the data transmission device 2 are respectively connected with a power module, the power module is powered by a lithium battery, the flexible sensor is connected with the amplifying circuit of the data transmission device 2 through an independent shielding lead, and the data analysis module of the data transmission device 2 adopts an STM32 processor.
The invention provides a health index dynamic monitoring system based on an intelligent seat backrest, which is characterized in that: the intelligent seat comprises a flexible sensor 3 of an intelligent seat backrest, a data transmission device 2, a cloud platform, an automobile intelligent ECU system and a terminal; the cloud platform is connected with a wireless network module and a terminal of the data transmission device 2 in a wireless mode; the intelligent automobile ECU system is connected with the wireless network module of the data transmission device 2 in a wireless mode; the wireless mode is WIFI; the terminal is a mobile phone.
A health index dynamic monitoring system based on an intelligent seat backrest and a data processing method of the data processing method thereof are characterized by comprising the following steps:
the method comprises the following steps: the flexible sensor 3 of the intelligent seat backrest collects signals formed by body fitting pressure of a driver, and the signals are transmitted to the STM32 processor through the amplifying circuit;
step two: the STM32 processor counts continuously transmitted signals of the same sensor within a period of time, compares the statistical data of all the flexible sensors 3, and takes the signal intensity variation amplitude within a set range as a stable signal, in the embodiment, the flexible sensor B2 is determined as a main sensor for monitoring the heart rate and the respiratory rate of a driver, and preliminary analysis and filtration are carried out on the amplified signal of B2 to remove interference signals;
step three: the data without interference is sent to a cloud platform through a wireless network module, the cloud platform analyzes the signals through a signal processing algorithm, the breathing rate and the heart rate are separated and identified, and the body state of the driver is judged according to the identified values of the heart rate and the breathing rate; setting the heart rate at 60-100 times/min and the respiration at 16-20 times/min according to the corresponding heart rate and respiration rate in different physical states, wherein the heart rate and the respiration rate are regular states; the heart rate is more than 100 times/min, the respiration is more than 20 times/min, and the heart rate and the respiration are regularly in a fatigue driving state; the heart rate is at 100-;
step four: the cloud platform sends the heart rate and respiratory rate data of the driver to the mobile phone terminal; when a driver is in a fatigue driving state or an atrial fibrillation state, the cloud platform sends voice reminding or warning to the mobile phone terminal; or the cloud platform sends the voice reminding or warning signal to the automobile intelligent ECU system through the wireless network module, and performs voice broadcast and takes corresponding measures according to the control setting of the automobile intelligent ECU system on the loudspeaker, the brake and the lighting system;
step five: the STM32 processor counts the working time of the flexible sensor, if the working time exceeds 3.5 hours and the driving is judged to be fatigue, the information is sent to the cloud platform, the cloud platform transmits warning information to the mobile phone terminal or the automobile intelligent ECU system, and the mobile phone terminal or the automobile intelligent ECU system sends out voice reminding or warning;
step six: data such as the heart rate of a driver are counted and analyzed for a long time, and health reports are pushed to a mobile phone terminal every week, so that the driver can know the physical state of the driver and can make a prejudgment on potential diseases;
step seven: the STM32 processor counts the signal voltage measured by each flexible sensor within a period of time, takes the time period of the signal variation range of each flexible sensor in the period of time as a reference time period, takes the voltage average value of each flexible sensor in the period of time as a reference value for judging the driving habit, such as setting the reference time period T0-T1 (T0 is the starting time of the reference time period, T1 is the ending time of the reference time period), taking the average value P of the feedback voltage of the sensor in the period of time as the reference value, taking the average value P of the voltage of each flexible sensor in a period of time in which the signal fluctuates as the comparison value for judging the driving habit, such as setting the comparison fluctuation time period T2-T3 (T2 is the starting time of the relative fluctuation time period, T3 is the ending time of the relative fluctuation time period), the average value P' of the feedback voltage of the flexible sensor, the average value of the pressure signal corresponding to each flexible sensor is as follows:
Figure 155468DEST_PATH_IMAGE002
step eight: during driving, when all P 'is reduced compared to the reference value, i.e. when P'A3< PA3And P'B3< PB3And P'C3< P'C3And P'A2< PA2And P'B2< PB2And P'C2< PC2When the vehicle is judged to be braked suddenly or braked, the maximum value of all sensors | P '-P | is taken, when | P' -P | is more than or equal to a threshold value I, the vehicle is braked suddenly, and a threshold value II is adopted<|P'-P|<The threshold value I is normal braking; when all P 'is increased, i.e. when P'A3>PA3And P'B3>PB3And P'C3> PC3And P'A2> PA2And P'B2> PB2And P'C2> PC2When the fuel is rapidly refueled or refueled, the maximum value of all sensors P '-P is taken, when P' -P is more than or equal to a threshold I, the fuel is rapidly refueled, and a threshold II is adopted<|P'-P|<The threshold I is oiling, in the embodiment, the threshold I is not less than 3.3V, and the threshold II is not more than 2.0V;
step nine: in the driving process, the pressure average value of the feedback signals of the flexible sensors on the left column is increased and the pressure average value of the feedback signals of the flexible sensors on the right column is reduced by comparing with the reference value, namely when P'C3> PC3And P'C2> PC2And P'C1> PC1And P'A3< PA3And P'A2< PA2And P'A2< PA2When the STM32 processor is judged to turn left, otherwise, when P'C3< PC3And P'C2< PC2And P'C1< PC1And P'A3> PA3And P'A2> PA2And P'A2> PA2When the sensor is in the right turn, the STM32 processor judges the sensor to turn right, the maximum value of all the sensors is taken, when the absolute value of P' -P is more than or equal to a threshold value I, the sensor is in a sharp turn, and a threshold value II is adopted<| P'-P|<The threshold value I is normal turning;
step ten: during driving, compared with a reference value, the average value of the row and column signal pressure sensed by the flexible sensor matrix is increased or reduced unevenly, and the STM32 processor judges that the driver is in an abnormal sitting posture, such as when P'A2> PA2And P'B2> PB2And P'C2> PC2And P'A1< PA1And P'B1< PB1And P'C1< PC1Judging that the driver slides down in the sitting posture;
step eleven: the STM32 processor transmits driving behavior information in the driving process to the cloud platform through the wireless network module, the cloud platform transmits the driving behavior in the driving process to the mobile phone terminal and carries out voice reminding on improper driving behaviors, or the cloud platform transmits the driving behavior to the automobile intelligent ECU system through the wireless network module and carries out voice reminding on improper driving behaviors through a loudspeaker; the STM32 processor gathers and counts the driver's driving behavior, analyzes out driver's driving habit through the algorithm and sends to the cell-phone terminal, helps correcting the potential unsafe factor of driver driving in-process, forms good driving habit, safe driving.
According to the dynamic health index monitoring system based on the intelligent seat backrest and the data processing method thereof, the system for monitoring the body health index of the driver is combined with the intelligent seat backrest, so that the functions of actively monitoring the heart rate and the respiratory rate of the driver, reminding and warning fatigue driving and body abnormity and analyzing driving habits are realized. Through long-term data acquisition and analysis, form driver's health archives, driving habit archives, discover in time that driver's health state is unusual, foresee potential disease, reduced the proruption risk of disease, correct driver's driving habit, drive safely civilized.

Claims (8)

1. An intelligent seat back, its characterized in that: the backrest cover comprises a backrest framework, a backrest cover sleeve (1) is sleeved on the framework, a flexible sensor (3) and a data transmission device (2) are fixed between the backrest framework and the backrest cover sleeve (1), and the flexible sensor (3) is one or a combination of two or more of a polymer piezoelectric sensor, a polymer piezoresistive sensor or an inorganic ceramic material pressure sensor; the flexible sensor (3) is connected with the data transmission device (2) by using a shielded wire; the data transmission device (2) comprises an amplifying circuit, a data analysis module and a wireless network module, wherein the amplifying circuit, the data analysis module and the wireless network module of the data transmission device (2) are respectively connected with a power supply module, and the power supply module is powered by a lithium battery or an external power supply.
2. The smart seat back of claim 1, wherein: the flexible sensors (3) are distributed on the backrest in a matrix form.
3. The smart seat back of claim 2, wherein: the number of the flexible sensors (3) is at least 3 rows and 3 columns.
4. The smart seat back of claim 1, wherein: the flexible sensor (3) adopts SS-S001 model.
5. The smart seat back of claim 1, wherein: the flexible sensor (3) is connected with an amplifying circuit of the data transmission device (2) through an independent shielding lead.
6. The smart seat back of claim 1, wherein: the data analysis module of the data transmission apparatus (2) employs an STM32 processor.
7. A dynamic health index monitoring system based on the intelligent seat backrest of claim 1, characterized in that: the intelligent seat comprises a flexible sensor (3) of an intelligent seat backrest, a data transmission device (2), a cloud platform, a vehicle intelligent system and a terminal; the cloud platform is connected with a wireless network module and a terminal of the data transmission device (2) in a wireless mode; the intelligent vehicle system is connected with a wireless network module of the data transmission device (2) in a wired or wireless mode; the wireless mode is WIFI or an intelligent vehicle networking system network; the terminal is any one of a vehicle-mounted large screen, a mobile phone, a PAD and a computer.
8. The data processing method of the dynamic health index monitoring system according to claim 7, comprising the steps of:
the method comprises the following steps: a flexible sensor (3) of the intelligent seat backrest collects signals formed by body fitting pressure of a driver, and the signals are transmitted to a data analysis module through an amplifying circuit;
step two: the data analysis module counts signals continuously transmitted by the same sensor within a period of time, compares the statistical data of all the flexible sensors (3), takes the signals with the variation amplitude within a set range as stable signals, determines the flexible sensors (B2) as main sensors for monitoring the heart rate and the respiratory rate of a driver, performs preliminary analysis and filtration on the amplified signals of the main sensors, and removes interference signals;
step three: the data without interference is sent to a cloud platform through a wireless network module, the cloud platform analyzes the signals through a signal processing algorithm, the breathing rate and the heart rate are separated and identified, and the body state of the driver is judged according to the identified values of the heart rate and the breathing rate; setting the heart rate at 60-100 times/min and the respiration at 16-20 times/min according to the corresponding heart rate and respiration rate in different physical states, wherein the heart rate and the respiration rate are regular states; the heart rate is more than 100 times/min, the respiration is more than 20 times/min, and the heart rate and the respiration are regularly in a fatigue driving state; the heart rate is at 100-;
step four: the cloud platform sends the heart rate and respiratory rate data of the driver to the terminal; when a driver is in a fatigue driving state or an atrial fibrillation state, the cloud platform sends voice reminding or warning to the terminal; or the cloud platform sends the voice reminding or warning signal to the intelligent vehicle system through the wireless network module, and performs voice broadcast and takes corresponding measures according to the control setting of the intelligent vehicle system on the loudspeaker, the brake and the lighting system;
step five: the data analysis module counts the working time of the flexible sensor (3), if fatigue driving is judged to be caused after 3.5 hours, the information is sent to the cloud platform, the cloud platform transmits warning information to the terminal or the intelligent vehicle system, and the terminal or the intelligent vehicle system sends out voice reminding or warning;
step six: data such as the heart rate of a driver are counted and analyzed for a long time, and health reports are pushed to a terminal every week, so that the driver can know the physical state of the driver and can make a prejudgment on potential diseases;
step seven: the data analysis module counts the voltage of the signal measured by each flexible sensor within a period of time, takes the time period of the signal variation amplitude of each flexible sensor within a set range as a reference time period, and takes the voltage average value P of each flexible sensor in the time period as a reference value for judging the driving habit; taking an average value P' of voltage values of all the flexible sensors in a certain time period when the signals fluctuate as a comparison value for judging the driving habits;
step eight: in the driving process, when all P 'is reduced relative to a reference value, the data analysis module judges that sudden braking or braking occurs, the maximum value of all sensors | P' -P | is taken, when | P '-P | is more than or equal to a threshold I, the sudden braking occurs, and the threshold II < | P' -P | < the threshold I is normal braking; when all P ' is increased, judging that quick refueling or refueling is carried out, when P ' -P is more than or equal to a threshold I, carrying out quick refueling, and when the threshold II < | P ' -P | < the threshold I, carrying out refueling;
step nine: in the driving process, relative to a reference value, the left row of flexible sensors P 'is increased, the right row of flexible sensors P' is decreased, the data analysis module judges that the vehicle turns left, and otherwise, the vehicle turns right; taking the maximum value of all sensors | P ' -P |, wherein when | P ' -P | > is more than or equal to a threshold I, the sensor is in sharp turning, and a threshold II < | P ' -P | < threshold I is in normal turning;
step ten: in the driving process, compared with a reference value, imbalance is increased or reduced in row and column signals sensed by the flexible sensor (3) matrix compared with the reference value, and the data analysis module judges that the driver is in an abnormal sitting posture;
step eleven: the data analysis module transmits driving behavior information in the driving process to the cloud platform through the wireless network module, the cloud platform transmits the driving behavior in the driving process to the terminal and carries out voice reminding on improper driving behaviors, or the cloud platform transmits the driving behavior to the intelligent system of the vehicle through the wireless network module and carries out voice reminding on improper driving behaviors through a loudspeaker; and the cloud end platform collects and counts the driving behavior in the driving process, analyzes the driving habit of the driver through an algorithm and transmits the driving habit to the terminal.
CN202110213567.7A 2021-02-26 2021-02-26 Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof Pending CN113057605A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110213567.7A CN113057605A (en) 2021-02-26 2021-02-26 Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110213567.7A CN113057605A (en) 2021-02-26 2021-02-26 Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof

Publications (1)

Publication Number Publication Date
CN113057605A true CN113057605A (en) 2021-07-02

Family

ID=76559043

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110213567.7A Pending CN113057605A (en) 2021-02-26 2021-02-26 Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof

Country Status (1)

Country Link
CN (1) CN113057605A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114906265A (en) * 2022-05-07 2022-08-16 无锡市金邦电动车制造有限公司 Intelligent scooter based on Internet of things
CN116399331A (en) * 2023-06-08 2023-07-07 太原理工大学 Remote control state monitoring device and monitoring method for excavator driver

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6392550B1 (en) * 2000-11-17 2002-05-21 Ford Global Technologies, Inc. Method and apparatus for monitoring driver alertness
US6506153B1 (en) * 1998-09-02 2003-01-14 Med-Dev Limited Method and apparatus for subject monitoring
CN102407805A (en) * 2010-09-20 2012-04-11 天津职业技术师范大学 Real-time monitoring system for state of automobile driver
CN105590466A (en) * 2016-03-14 2016-05-18 重庆邮电大学 Monitoring system and monitoring method for dangerous operation behaviors of driver on cloud platform
US20170327124A1 (en) * 2016-05-10 2017-11-16 Samsung Electronics Co., Ltd. Electronic device and method for determining a state of a driver
CN110074769A (en) * 2013-09-05 2019-08-02 提爱思科技股份有限公司 Seat
CN112193251A (en) * 2020-10-13 2021-01-08 一汽解放汽车有限公司 Driving posture feedback system and method for driver

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6506153B1 (en) * 1998-09-02 2003-01-14 Med-Dev Limited Method and apparatus for subject monitoring
US6392550B1 (en) * 2000-11-17 2002-05-21 Ford Global Technologies, Inc. Method and apparatus for monitoring driver alertness
CN102407805A (en) * 2010-09-20 2012-04-11 天津职业技术师范大学 Real-time monitoring system for state of automobile driver
CN110074769A (en) * 2013-09-05 2019-08-02 提爱思科技股份有限公司 Seat
CN105590466A (en) * 2016-03-14 2016-05-18 重庆邮电大学 Monitoring system and monitoring method for dangerous operation behaviors of driver on cloud platform
US20170327124A1 (en) * 2016-05-10 2017-11-16 Samsung Electronics Co., Ltd. Electronic device and method for determining a state of a driver
CN112193251A (en) * 2020-10-13 2021-01-08 一汽解放汽车有限公司 Driving posture feedback system and method for driver

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114906265A (en) * 2022-05-07 2022-08-16 无锡市金邦电动车制造有限公司 Intelligent scooter based on Internet of things
CN116399331A (en) * 2023-06-08 2023-07-07 太原理工大学 Remote control state monitoring device and monitoring method for excavator driver
CN116399331B (en) * 2023-06-08 2023-08-08 太原理工大学 Remote control state monitoring device and monitoring method for excavator driver

Similar Documents

Publication Publication Date Title
Sikander et al. Driver fatigue detection systems: A review
Doudou et al. Driver drowsiness measurement technologies: Current research, market solutions, and challenges
CN104146722B (en) Driving fatigue detecting and grading early warning method based on head signals
CN104840204B (en) A kind of fatigue driving monitoring method and equipment
US10864918B2 (en) Vehicle and method for supporting driving safety thereof
CN106691443B (en) Wearable driver fatigue-prevention intelligent monitoring and early warning system based on electroencephalogram
CN113057605A (en) Intelligent seat backrest-based health index dynamic monitoring system and data processing method thereof
Li et al. A method for fatigue detection based on Driver's steering wheel grip
US20150088397A1 (en) Vigilance Monitoring System
CN113071446A (en) Health index monitoring system based on automobile intelligent safety belt and data processing method thereof
US20200241525A1 (en) Computer-based apparatus system for assessing, predicting, correcting, recovering, and reducing risk arising from an operator?s deficient situation awareness
CN103021134A (en) Monitoring and alarm device for fatigue driving of automobile
Doudou et al. A light on physiological sensors for efficient driver drowsiness detection system
CN105534531A (en) Method and system for preventing fatigue driving
Tripathy et al. An application of wireless brain–computer interface for drowsiness detection
CN109949923A (en) A kind of vehicle-mounted health system
KR101988426B1 (en) Wrist type electricshock apparatus for preventing sleepiness
TWI337587B (en) System for health management used in vehicle and method thereof
CN202960535U (en) Automobile fatigue driving monitoring alarm device
Kundinger et al. A robust drowsiness detection method based on vehicle and driver vital data
KR20120121074A (en) A earlobe wearable system of shaking off sleepiness
CN107358785A (en) A kind of bus driver fatigue detection device
CN115959138A (en) Driver rescue method, device and system based on physiological data
Čolić et al. Driver drowsiness detection and measurement methods
CN203849834U (en) Driving fatigue alerting device

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20210702