CN116035579B - Ship driver fatigue evaluation system and method - Google Patents

Ship driver fatigue evaluation system and method Download PDF

Info

Publication number
CN116035579B
CN116035579B CN202310202258.9A CN202310202258A CN116035579B CN 116035579 B CN116035579 B CN 116035579B CN 202310202258 A CN202310202258 A CN 202310202258A CN 116035579 B CN116035579 B CN 116035579B
Authority
CN
China
Prior art keywords
time
fatigue
driver
frequency domain
signals
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.)
Active
Application number
CN202310202258.9A
Other languages
Chinese (zh)
Other versions
CN116035579A (en
Inventor
牛振
冯旭
丁猛
邵壮超
黄建松
翟宇佳
孙久一
甘国林
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.)
Chinese Peoples Liberation Army Naval Characteristic Medical Center
Original Assignee
Chinese Peoples Liberation Army Naval Characteristic Medical Center
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 Chinese Peoples Liberation Army Naval Characteristic Medical Center filed Critical Chinese Peoples Liberation Army Naval Characteristic Medical Center
Priority to CN202310202258.9A priority Critical patent/CN116035579B/en
Publication of CN116035579A publication Critical patent/CN116035579A/en
Application granted granted Critical
Publication of CN116035579B publication Critical patent/CN116035579B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
    • G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
    • 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
    • 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
    • A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/168—Evaluating attention deficit, hyperactivity
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/18—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state for vehicle drivers or machine operators
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802—Sensor mounted on worn items
    • A61B5/681—Wristwatch-type devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • Biophysics (AREA)
  • Veterinary Medicine (AREA)
  • Public Health (AREA)
  • Surgery (AREA)
  • Molecular Biology (AREA)
  • Medical Informatics (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • Psychiatry (AREA)
  • Physiology (AREA)
  • Cardiology (AREA)
  • Developmental Disabilities (AREA)
  • Signal Processing (AREA)
  • Psychology (AREA)
  • Hospice & Palliative Care (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Child & Adolescent Psychology (AREA)
  • General Physics & Mathematics (AREA)
  • Social Psychology (AREA)
  • Educational Technology (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Pulmonology (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Human Computer Interaction (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The invention discloses a ship driver fatigue evaluation system and a ship driver fatigue evaluation method, wherein fatigue state does not appear in the initial stage of driving a ship by a driver, so that the fatigue state of the driver is not evaluated in the initial stage, if the driver is replaced in the initial stage, the new driver needs to be reckoned in the initial stage, the fatigue state of the driver is not evaluated in the initial stage, and if the driver is not replaced in the initial stage, the fatigue state of the driver is evaluated after the initial stage, and the design can reduce data processing capacity. In the invention, whether the driver is in an awake state or a fatigue state is firstly judged, when the driver is in the awake state, whether the driver is in the awake state or the fatigue state in the next second set time period is judged, and when the driver is in the fatigue state, the driver is further judged to be in the fatigue state of which level is specifically, and the design can reduce the data processing capacity.

Description

Ship driver fatigue evaluation system and method
Technical Field
The invention relates to the technical field of fatigue detection of ship drivers, in particular to a system and a method for fatigue evaluation of ship drivers.
Background
The driver keeps the driving state for a long time and is easy to generate fatigue state, fatigue is easy to cause serious accidents, and the driver is monitored to be in the fatigue state and timely reminded of being capable of effectively preventing accidents. The existing driver fatigue driving monitoring technology mainly collects face images of drivers in an image collection mode, and then judges and analyzes whether the behaviors such as yawning, low head, eye closing and the like exist according to collected image information, so that a conclusion whether the drivers have fatigue driving or not is obtained. There are also technologies for monitoring the fatigue state of a driver based on the continuous driving time of the driver.
For ship drivers, the initial driving state is just to start driving, so that the condition of driving fatigue generally does not occur, the fatigue monitoring is carried out from the beginning almost without considering the factor in the prior art, and the data processing capacity is greatly increased; moreover, as the ship can stop at a certain position on water for operation, the ship is in a relatively static state, and accidents can not be caused even if a driver is in a fatigue state, so that the fatigue state of the driver is not required to be monitored at the moment, or the driver is replaced in the driving process, the fatigue state of the new driver is required to be judged again, and the occurrence of the situations is not considered in the conventional fatigue state monitoring technology of the driver, so that the data processing capacity is greatly increased.
Disclosure of Invention
Aiming at the problems and defects existing in the prior art, the invention provides a fatigue evaluation system and method for ship drivers.
The invention solves the technical problems by the following technical proposal:
the invention provides a ship driver fatigue evaluation system which is characterized by comprising a camera, a head-mounted electroencephalogram signal acquisition component, an intelligent bracelet and a fatigue evaluation component, wherein the camera is arranged on an operation desk of a cab and is positioned in front of a driver.
The head-mounted electroencephalogram signal acquisition assembly comprises a flexible shell which is attached to the forehead of a driver and an elastic binding belt which is bound to the head of the driver, wherein two ends of the elastic binding belt are respectively fixed with two ends of the flexible shell, an electroencephalogram sensor is respectively arranged on the left, middle and right sides in the flexible shell, and a first micro controller and a first wireless communication module are further arranged in the flexible shell.
The intelligent bracelet comprises a bracelet body, wherein a pulse sensor, a temperature sensor, a second micro-controller and a second wireless communication module are arranged on the bracelet body.
The fatigue evaluation component includes a speed sensor, an ambient noise sensor, a control module, and a third wireless communication module.
The control module is used for starting timing after work is started, controlling and receiving face images of a driver acquired by the camera at intervals of a fixed time period (such as 30 seconds), carrying out identity recognition on the driver based on the face images, judging whether the identity recognition information is changed in a first set time period (such as 30 minutes) from starting timing, restarting timing with the judgment of the change time as a starting point when judging the change, acquiring the face images and the identity recognition, and simultaneously transmitting a signal acquisition instruction to the head-mounted electroencephalogram signal acquisition assembly and the intelligent bracelet by utilizing the third wireless communication module when judging the change.
The control module is used for controlling the speed sensor to detect the ship speed value and the signal acquisition time stamp thereof in real time.
The control module is used for controlling the environmental noise sensor to detect the environmental noise value and the signal acquisition time stamp thereof in real time.
The first micro controller is used for respectively controlling the left-middle-right side electroencephalogram sensors to acquire left-middle-right side electroencephalogram signals and signal acquisition time stamps thereof in real time after receiving signal acquisition instructions by utilizing the first wireless communication module, and transmitting the signals to the control module by utilizing the first wireless communication module and the third wireless communication module.
The second microcontroller is used for controlling the pulse sensor to collect pulse signals and signal collection time stamps thereof in real time after receiving the signal collection instruction by utilizing the second wireless communication module, controlling the temperature sensor to collect wrist temperature signals and signal collection time stamps thereof in real time, and transmitting the signals to the control module by utilizing the second wireless communication module and the third wireless communication module.
The control module is used for judging whether the speed value is zero in a second set time period (such as 10 minutes) and whether the identity identification information is changed in the second set time period (such as 10 minutes), judging whether the speed value is zero again by taking the time of the follow-up speed which is not zero as the starting point when the speed value is zero, restarting timing, collecting facial images and identifying the identity by taking the judging changing time as the starting point when the identity identification information is changed, and preprocessing the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals when the speed value is not zero.
The control module is used for extracting characteristics of the preprocessed environmental noise signals, the preprocessed electroencephalogram signals, the preprocessed pulse signals and the preprocessed wrist temperature signals so as to sequentially extract time domain characteristics and frequency domain characteristics of the environmental noise signals, the preprocessed electroencephalogram signals, the preprocessed pulse signals and preprocessed wrist temperature signals.
The control module is used for respectively matching the environmental noise signal time/frequency domain characteristics, the electroencephalogram signal average time/frequency domain characteristics, the pulse signal time/frequency domain characteristics and the wrist temperature signal time/frequency domain characteristics with the awake range set and the fatigue range set to determine whether a driver is in an awake state or in a fatigue state, and entering a next second set time period for judgment when the driver is in the awake state.
The control module is used for matching the time/frequency domain characteristics of the environmental noise signals, the average time/frequency domain characteristics of the brain electrical signals, the time/frequency domain characteristics of the pulse signals and the time/frequency domain characteristics of the wrist temperature signals with the corresponding characteristics in each fatigue level when the driver is in a fatigue state, and determining the specific fatigue level of the driver.
The invention also provides a ship driver fatigue evaluation method, which is characterized by being realized by the ship driver fatigue evaluation system, and comprises the following steps:
s1, starting timing after starting work, controlling and receiving face images of a driver acquired by a camera at intervals of a fixed time period (such as 30 seconds), identifying the driver based on the face images, judging whether the identification information is changed in a first set time period (such as 30 minutes) from starting timing, repeatedly executing the step S1 with the change time being judged as a starting point when the change is judged, and entering the step S2 when the change is not judged.
S2, the control module simultaneously sends a signal acquisition instruction to the head-mounted electroencephalogram signal acquisition component and the intelligent bracelet by utilizing the third wireless communication module.
S3, the control module controls the speed sensor to detect the ship speed value and the signal acquisition time stamp thereof in real time.
The control module controls the environmental noise sensor to detect the environmental noise value and the signal acquisition time stamp in real time.
And the first microcontroller is used for respectively controlling the left-middle-right side electroencephalogram sensors to acquire left-middle-right side electroencephalogram signals and signal acquisition time stamps thereof in real time after receiving the signal acquisition instructions by using the first wireless communication module, and transmitting the signals to the control module by using the first wireless communication module and the third wireless communication module.
And after receiving the signal acquisition instruction by the second micro controller through the second wireless communication module, controlling the pulse sensor to acquire the pulse signal and the signal acquisition time stamp thereof in real time, controlling the temperature sensor to acquire the wrist temperature signal and the signal acquisition time stamp thereof in real time, and transmitting the wrist temperature signal and the signal acquisition time stamp thereof to the control module through the second wireless communication module and the third wireless communication module.
S4, the control module judges whether the speed value is zero in a second set time period (such as 10 minutes) and whether the identity information is changed in the second set time period (such as 10 minutes), when the speed value is zero, the control module re-executes the step S4 by taking the moment of the follow-up speed which is not zero as a starting point, when the identity information is changed, the control module re-executes the step S1 by taking the moment of the change as the starting point, and when the identity information is not changed, the control module enters the step S5.
S5, the control module performs preprocessing operation on the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals.
And S6, the control module performs feature extraction on the preprocessed environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals so as to sequentially extract time domain features and frequency domain features of the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals.
And S7, the control module respectively matches the environmental noise signal time/frequency domain characteristics, the electroencephalogram signal average time/frequency domain characteristics, the pulse signal time/frequency domain characteristics and the wrist temperature signal time/frequency domain characteristics with the awake range set and the fatigue range set to determine whether the driver is in an awake state or in a fatigue state, and enters a next second set time period to repeatedly execute the step S4 when the driver is in the awake state, and enters the step S8 when the driver is in the fatigue state.
And S8, the control module matches the time/frequency domain characteristics of the environmental noise signals, the average time/frequency domain characteristics of the electroencephalogram signals, the time/frequency domain characteristics of the pulse signals and the time/frequency domain characteristics of the wrist temperature signals with corresponding characteristics in each fatigue level, and determines the specific fatigue level of the driver.
According to the invention, the fatigue state of the driver can not appear in the initial stage of driving the ship, so that the fatigue state of the driver is not evaluated in the initial stage, if the driver is replaced in the initial stage, the new driver needs to be reckoned in the initial stage, the fatigue state of the driver is not evaluated in the initial stage, and if the driver is not replaced in the initial stage, the fatigue state of the driver is evaluated after the initial stage, so that the data processing capacity can be reduced.
In the invention, the driver is not directly and once judged in which fatigue state, but is firstly judged whether the driver is in a waking state or a fatigue state, and the driver is judged whether the driver is in the waking state or the fatigue state in the next second set time period when the driver is judged to be in the waking state, and the driver is further judged to be in the fatigue state of which level when the driver is judged to be in the fatigue state.
Drawings
FIG. 1 is a control block diagram of a ship operator fatigue assessment system according to a preferred embodiment of the present invention.
Fig. 2 is a schematic structural diagram of a headset electroencephalogram signal acquisition component according to a preferred embodiment of the present invention.
FIG. 3 is a flowchart of a method for fatigue assessment of ship operators according to a preferred embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1 and 2, the present embodiment provides a fatigue evaluation system for ship drivers, which includes a camera 1, a head-mounted electroencephalogram signal acquisition component 2, an intelligent bracelet 3, and a fatigue evaluation component 4.
The camera 1 is arranged on an operation table of a cab and is positioned in front of a driver.
As shown in fig. 2, the head-mounted electroencephalogram signal acquisition assembly 2 comprises a flexible shell 20 attached to the forehead of a driver and an elastic binding belt 21 bound to the head of the driver, the elastic binding belt 21 is adjustable, two ends of the elastic binding belt 21 are respectively fixed with two ends of the flexible shell 20, a left electroencephalogram sensor 22 is arranged on the left side in the flexible shell 20, a middle electroencephalogram sensor 23 is arranged on the middle side, a right electroencephalogram sensor 24 is arranged on the right side, a left pressure sensor 25 is arranged on the left side in the flexible shell 20, a middle pressure sensor 26 is arranged on the middle side, a right pressure sensor 27 is arranged on the right side in the flexible shell 20, and a first micro controller 28 and a first wireless communication module 29 are further arranged in the flexible shell 20.
The intelligent bracelet 3 comprises a bracelet body, wherein the bracelet body is provided with a pulse sensor 31, a temperature sensor 32, a second micro controller 33 and a second wireless communication module 34, and the structure of the intelligent bracelet 3 in the embodiment is the same as that of the existing intelligent bracelet.
The fatigue evaluation assembly 4 is arranged on an operation desk of the cab, and the fatigue evaluation assembly 4 comprises a speed sensor 41, an environment noise sensor 42, a control module 43 and a third wireless communication module 44.
The functions performed by the modules/components are specifically described below:
the head-mounted electroencephalogram signal acquisition assembly 2 is worn on the head, the flexible shell 20 is attached to the forehead of a driver, the left pressure sensor 25, the middle pressure sensor 26 and the right pressure sensor 27 are used for detecting the pressure between the corresponding side of the flexible shell 20 and the forehead skin, the left side pressure value, the middle side pressure value and the right side pressure value are transmitted to the first micro controller 28, and the first micro controller 28 transmits the left side pressure value, the middle side pressure value and the right side pressure value to the control module 43 through the first wireless communication module 29 and the third wireless communication module 44. The control module 43 determines whether any pressure value (left side pressure value, middle side pressure value and right side pressure value) is lower than a set pressure threshold, and sends out warning information of poor contact between the head-mounted electroencephalogram signal acquisition component and skin when any pressure value is lower than the set pressure threshold, so as to remind a driver that the head-mounted electroencephalogram signal acquisition component is not worn, and sends out warning information of good contact between the head-mounted electroencephalogram signal acquisition component and skin when all three pressure values (left side pressure value, middle side pressure value and right side pressure value) are not lower than the set pressure threshold. The intelligent bracelet 3 is then worn on the wrist of the driver.
The system starts working, the camera 1 collects face images of a driver every other fixed time period (such as 30 seconds), the control module 43 starts timing after the working is started, receives the face images of the driver collected by the camera 1, carries out identity recognition on the driver based on the face images, judges whether the identity recognition information changes in a first set time period (such as 30 minutes) from the starting timing, resumes timing, collecting the face images and the identity recognition with the change time being judged as a starting point when the change is judged, and simultaneously sends a signal collection instruction to the head-mounted brain electrical signal collection assembly and the intelligent bracelet by utilizing the third wireless communication module when the change is not judged. The control mechanism here is: the fatigue state should not occur at the initial stage of the driving of the ship by the driver, so that the fatigue state evaluation of the driver is not performed for a first set period of time, for example, 30 minutes after the driving. If the driver is replaced in the time period, the new driver needs to be reckoned for a first set time period, such as 30 minutes after driving, and no fatigue state evaluation of the driver is performed.
If the driver is not replaced within a first set period of time, such as 30 minutes after driving, the driver is subjected to fatigue state assessment: the control module 43 controls the speed sensor 41 to detect the ship speed value and the signal acquisition time stamp thereof in real time, and controls the environmental noise sensor 42 to detect the environmental noise value and the signal acquisition time stamp thereof in real time; after the first microcontroller 28 receives the signal acquisition instruction by using the first wireless communication module 29, the left electroencephalogram sensor 22, the middle electroencephalogram sensor 23 and the right electroencephalogram sensor 24 are respectively controlled to acquire left, middle and right electroencephalogram signals and signal acquisition time stamps thereof in real time, and the signals are transmitted to the control module 43 by using the first wireless communication module 29 and the third wireless communication module 44; after receiving the signal acquisition command by the second wireless communication module 34, the second microcontroller 33 controls the pulse sensor 31 to acquire the pulse signal and the signal acquisition time stamp thereof in real time, controls the temperature sensor 32 to acquire the wrist temperature signal and the signal acquisition time stamp thereof in real time, and transmits the signals to the control module 43 by the second wireless communication module 34 and the third wireless communication module 44.
The control module 43 determines whether a speed value is zero in a second set period of time (e.g., 10 minutes), if the speed value is zero, the ship is not running, and the fatigue state of the driver is not evaluated, and if the speed is detected to be non-zero, the control module re-determines whether the speed is zero in the second set period of time from the time when the speed is not zero. The control module 43 determines whether the identification information is changed within a second set period of time (e.g., 10 minutes), and resumes timing, collecting facial images and identification with the determined change time as a start point when the identification information is changed, and performs preprocessing operation on the environmental noise signal, each brain electrical signal, pulse signal and wrist temperature signal when the above two conditions do not occur. The control mechanism here is: and if the ship does not travel or the driver changes the personnel within the second set time period (such as 10 minutes), the fatigue state analysis is not further carried out.
The specific pretreatment operation is as follows: the control module 43 performs normalization processing on the environmental noise signal, the left brain electrical signal, the middle brain electrical signal, the right brain electrical signal, the pulse signal, and the wrist temperature signal, and performs noise reduction filtering processing on the environmental noise signal, the left brain electrical signal, the middle brain electrical signal, the right brain electrical signal, the pulse signal, and the wrist temperature signal after normalization processing.
Extracting the characteristics of each preprocessed signal: the control module 43 performs feature extraction on the preprocessed ambient noise signal, each electroencephalogram signal, pulse signal, and wrist temperature signal to sequentially extract time domain features and frequency domain features of the ambient noise signal, left electroencephalogram signal, middle electroencephalogram signal, right electroencephalogram signal, pulse signal, and wrist temperature signal, respectively.
The control module 43 matches the environmental noise signal time/frequency domain feature, the electroencephalogram signal average time/frequency domain feature (the electroencephalogram signal average time domain feature refers to an average value of corresponding time domain features of left, middle and right electroencephalogram signals, and the electroencephalogram signal average frequency domain feature refers to an average value of corresponding frequency domain features of left, middle and right electroencephalogram signals), the pulse signal time/frequency domain feature, and the wrist temperature signal time/frequency domain feature with the awake range set and the fatigue range set, respectively, one by one, to determine whether the driver is awake or in fatigue, and enters a next second set period of time to determine when the driver is awake.
The specific matching process is as follows: when the time/frequency domain characteristic value of a certain signal is positioned in the corresponding characteristic range in the awake range set or the fatigue range set, the awake range set or the fatigue range set is successfully matched once, the number of successful matches in the awake range set and the fatigue range set is counted, the number of successful matches in the awake range set and the number of successful matches in the fatigue range set are judged, when the corresponding number of the awake range set is larger than the corresponding number of the fatigue range set, the driver is judged to be in an awake state, then the next second set time period is entered for judgment, when the corresponding number of the fatigue range set is larger than the corresponding number of the awake range set, the driver is judged to be in a fatigue state, and the specific fatigue level of the driver is further judged.
If the time domain feature A of the environmental noise signal is positioned in the corresponding feature range in the awake range set, the awake range set is successfully matched once, the initial value of the successful number of the awake range set is 0, and if the awake range set is successfully matched once, the value is correspondingly added with 1. And if the frequency domain characteristic B of the environmental noise signal is positioned in the corresponding characteristic range in the awake range set, the awake range set is successfully matched once, and the number of times of successful matching in the awake range set is increased by 1.
The method does not judge which fatigue state the driver is in at one time, but judges whether the driver is in an awake state or a fatigue state first, judges whether the driver is in the awake state or the fatigue state in the next second set time period when the driver is in the awake state, and further judges which level of fatigue state the driver is in when the driver is in the fatigue state.
The control module 43 matches the environmental noise signal time/frequency domain feature, the electroencephalogram signal average time/frequency domain feature, the pulse signal time/frequency domain feature and the wrist temperature signal time/frequency domain feature with corresponding features in each fatigue level one by one when in a fatigue state, and determines the specific fatigue level of the driver.
The specific matching process is as follows: when the time/frequency domain characteristic value of a certain signal is positioned in the corresponding characteristic range in a certain fatigue level, the fatigue level is successfully matched once, the number of successful matches in each fatigue level is counted, the psychological stress level probability corresponding to the set number range of successful matches to which the number of successful matches belongs is inquired, and the pressure level probability with the largest numerical value is displayed, so that the specific fatigue level of a driver and the probability thereof are determined.
As shown in fig. 3, the present embodiment further provides a method for evaluating fatigue of a ship driver, which is implemented by using the fatigue evaluation system for a ship driver, and the method includes the following steps:
step 101, the control module starts timing after starting the work, controls and receives the face image of the driver acquired by the camera at intervals of a fixed time period (for example, 30 seconds), carries out identity recognition on the driver based on the face image, judges whether the identity recognition information is changed in a first set time period (for example, 30 minutes) from starting timing, repeatedly executes step 101 with the judging change time as a starting point when judging the change, and enters step 102 when judging the non-change;
step 102, the control module simultaneously sends a signal acquisition instruction to the head-mounted electroencephalogram signal acquisition component and the intelligent bracelet by utilizing a third wireless communication module;
step 103, the control module controls the speed sensor to detect the ship speed value and the signal acquisition time stamp thereof in real time;
the control module controls the environmental noise sensor to detect the environmental noise value and the signal acquisition time stamp in real time;
the first microcontroller receives the signal acquisition instructions by using the first wireless communication module, and then respectively controls the left-middle-right side electroencephalogram sensors to acquire left-middle-right side electroencephalogram signals and signal acquisition time stamps thereof in real time, and transmits the signals to the control module by using the first wireless communication module and the third wireless communication module;
the second microcontroller receives the signal acquisition instruction by using the second wireless communication module, controls the pulse sensor to acquire the pulse signal and the signal acquisition time stamp thereof in real time, controls the temperature sensor to acquire the wrist temperature signal and the signal acquisition time stamp thereof in real time, and transmits the signals to the control module by using the second wireless communication module and the third wireless communication module;
step 104, the control module judges whether a speed value is zero in a second set time period (for example, 10 minutes), if yes, step 104 is re-executed with the time point when the subsequent speed is not zero as the starting point, and if no, step 105 is entered;
step 105, the control module determines whether the identification information is changed within a second set period of time (for example, 10 minutes), when the identification information is changed, the control module re-executes step 101 with the determined change time as the starting point, and if not, the control module proceeds to step 106.
Step 106, the control module performs preprocessing operation on the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals; the pretreatment operation is as follows: the control module performs normalization processing on the environmental noise signals, the electroencephalogram signals, the pulse signals and the wrist temperature signals respectively, and performs noise reduction filtering processing on the environmental noise signals, the electroencephalogram signals, the pulse signals and the wrist temperature signals after normalization processing.
And 107, the control module performs feature extraction on the preprocessed environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals to sequentially extract time domain features and frequency domain features of the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals.
Step 108, the control module matches the environmental noise signal time/frequency domain feature, the electroencephalogram signal average time/frequency domain feature, the pulse signal time/frequency domain feature and the wrist temperature signal time/frequency domain feature with the awake range set and the fatigue range set, respectively, determines whether the driver is awake or tired, enters the next second set time period when in awake state, repeatedly executes step 104, and enters step 109 when in fatigue state.
Step 109, the control module matches the time/frequency domain characteristics of the environmental noise signal, the average time/frequency domain characteristics of the electroencephalogram signal, the time/frequency domain characteristics of the pulse signal and the time/frequency domain characteristics of the wrist temperature signal with corresponding characteristics in each fatigue level, and determines the specific fatigue level of the driver.
Wherein step 108 comprises the steps of: the control module is used for respectively matching the environmental noise signal time/frequency domain characteristic, the brain electrical signal average time/frequency domain characteristic, the pulse signal time/frequency domain characteristic and the wrist temperature signal time/frequency domain characteristic with the corresponding characteristic in the awake range set and the corresponding characteristic in the fatigue range set one by one, if the time/frequency domain characteristic value of a certain signal is positioned in the corresponding characteristic range in the awake range set or the fatigue range set, the awake range set or the fatigue range set is successfully matched once, the number of successful matching in each of the awake range set and the fatigue range set is counted, the number of successful matching in the awake range set and the number of successful matching in the fatigue range set are judged, if the corresponding number of the awake range set is larger than the corresponding number of the fatigue range set, the driver is judged to be in the awake state, then the next second set time period is entered for judgment, and if the corresponding number of the fatigue range set is larger than the corresponding number of the awake range set, the driver is judged to be in the fatigue state, and the specific fatigue level of the driver is further judged.
Step 109 includes the steps of: the control module carries out one-to-one matching on the environmental noise signal time/frequency domain feature, the electroencephalogram signal average time/frequency domain feature, the pulse signal time/frequency domain feature and the wrist temperature signal time/frequency domain feature with the corresponding features in each fatigue level, if the time/frequency domain feature value of a certain signal is positioned in the corresponding feature range in a certain fatigue level, the fatigue level is successfully matched once, the number of successful matches in each fatigue level is counted, the psychological pressure level probability corresponding to the matching success set number range to which the number of successful matches belongs is inquired, and the pressure level probability with the largest numerical value is displayed, so that the specific fatigue level and the probability thereof of a driver are determined.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that these are by way of example only, and the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the invention, but such changes and modifications fall within the scope of the invention.

Claims (6)

1. The fatigue evaluation system for the ship drivers is characterized by comprising a camera, a head-mounted electroencephalogram signal acquisition component, an intelligent bracelet and a fatigue evaluation component;
the head-mounted electroencephalogram signal acquisition assembly comprises a flexible shell which is attached to the forehead of a driver and an elastic binding belt which is bound to the head of the driver, wherein two ends of the elastic binding belt are respectively fixed with two ends of the flexible shell, electroencephalogram sensors are respectively arranged on the left, middle and right sides in the flexible shell, and a first micro controller and a first wireless communication module are also arranged in the flexible shell;
the intelligent bracelet comprises a bracelet body, wherein a pulse sensor, a temperature sensor, a second micro controller and a second wireless communication module are arranged on the bracelet body;
the fatigue evaluation component comprises a speed sensor, an environmental noise sensor, a control module and a third wireless communication module;
the control module is used for starting timing after work is started, controlling and receiving face images of a driver acquired by the camera at intervals of a fixed time period, carrying out identity recognition on the driver based on the face images, judging whether identity recognition information is changed in a first set time period from starting timing, restarting timing by taking the judgment of the change time as a starting point when judging the change, acquiring the face images and carrying out identity recognition, and simultaneously transmitting a signal acquisition instruction to the head-mounted electroencephalogram signal acquisition component and the intelligent bracelet by utilizing the third wireless communication module when judging the change is not carried out;
the control module is used for controlling the speed sensor to detect the ship speed value and the signal acquisition time stamp thereof in real time;
the control module is used for controlling the environmental noise sensor to detect the environmental noise value and the signal acquisition time stamp in real time;
the first micro controller is used for respectively controlling the left middle-right side electroencephalogram sensors to acquire left middle-right side electroencephalogram signals and signal acquisition time stamps thereof in real time, and the left middle-right side electroencephalogram signals and the signal acquisition time stamps are transmitted to the control module by utilizing the first wireless communication module and the third wireless communication module;
the second micro controller is used for controlling the pulse sensor to acquire pulse signals and signal acquisition time stamps thereof in real time, controlling the temperature sensor to acquire wrist temperature signals and signal acquisition time stamps thereof in real time, and transmitting the wrist temperature signals and the signal acquisition time stamps thereof to the control module by utilizing the second wireless communication module and the third wireless communication module;
the control module is used for judging whether the speed value is zero in the second set time period and whether the identity identification information is changed in the second set time period, judging whether the speed value is zero in the second set time period again by taking the moment of the follow-up speed which is not zero as the starting point when the speed value is zero, restarting timing and collecting facial images and identity identification by taking the judging moment of the change as the starting point when the identity identification information is changed, and preprocessing the environmental noise signals, the electroencephalogram signals, the pulse signals and the wrist temperature signals when the speed value is zero;
the control module is used for extracting characteristics of the preprocessed environmental noise signals, the preprocessed electroencephalogram signals, the preprocessed pulse signals and the preprocessed wrist temperature signals so as to sequentially extract time domain characteristics and frequency domain characteristics of the environmental noise signals, the preprocessed electroencephalogram signals, the preprocessed pulse signals and preprocessed wrist temperature signals;
the control module is used for respectively matching the environmental noise signal time/frequency domain characteristics, the electroencephalogram signal average time/frequency domain characteristics, the pulse signal time/frequency domain characteristics and the wrist temperature signal time/frequency domain characteristics with an awake range set and a fatigue range set to determine whether a driver is in an awake state or in a fatigue state, and entering a next second set time period for judgment when the driver is in the awake state;
the control module is used for matching the time/frequency domain characteristics of the environmental noise signals, the average time/frequency domain characteristics of the electroencephalogram signals, the time/frequency domain characteristics of the pulse signals and the time/frequency domain characteristics of the wrist temperature signals with corresponding characteristics in various fatigue levels when the driver is in a fatigue state, and determining the specific fatigue level of the driver;
the control module is used for matching the environmental noise signal time/frequency domain characteristic, the electroencephalogram signal average time/frequency domain characteristic, the pulse signal time/frequency domain characteristic and the wrist temperature signal time/frequency domain characteristic with the corresponding characteristic in the awake range set and the corresponding characteristic in the fatigue range set one by one respectively, if the time/frequency domain characteristic value of a certain signal is positioned in the corresponding characteristic range in the awake range set or the fatigue range set, the awake range set or the fatigue range set is successfully matched once, the number of successful matching in each of the awake range set and the fatigue range set is counted, the number of successful matching in the awake range set and the number of successful matching in the fatigue range set are judged, if the corresponding number of the awake range set is larger than the corresponding number of the fatigue range set, the driver is judged to be in an awake state, if the corresponding number of the fatigue range set is larger than the corresponding number of the awake range set, the driver is judged to be in a fatigue state, and the specific fatigue level of the driver is further judged;
the control module is used for matching the time/frequency domain characteristics of the environmental noise signals, the average time/frequency domain characteristics of the electroencephalogram signals, the time/frequency domain characteristics of the pulse signals and the time/frequency domain characteristics of the wrist temperature signals with the corresponding characteristics in each fatigue level one by one when the time/frequency domain characteristic value of a certain signal is positioned in the corresponding characteristic range in a certain fatigue level, the fatigue level is successfully matched once, the number of successful matches in each fatigue level is counted, the fatigue level probability corresponding to the range of the set number of successful matches to which the number of successful matches belong is inquired, the fatigue level probability with the largest value is displayed, and the specific fatigue level where a driver is positioned and the probability thereof are determined.
2. The ship driver fatigue evaluation system according to claim 1, wherein the control module is configured to normalize the environmental noise signal, each electroencephalogram signal, the pulse signal, and the wrist temperature signal, and to perform noise reduction filtering processing on the normalized environmental noise signal, each electroencephalogram signal, the pulse signal, and the wrist temperature signal.
3. The ship driver fatigue evaluation system according to claim 1, wherein the elastic tie is an adjustable elastic tie, pressure sensors are respectively arranged on the left, middle and right sides in the flexible shell, each pressure sensor is used for detecting the pressure between the corresponding side of the flexible shell and the forehead skin, and transmitting each pressure value to a first micro controller, and the first micro controller is used for transmitting each pressure value to a control module through a first wireless communication module and a third wireless communication module;
the control module is used for judging whether any pressure value is lower than a set pressure threshold value, sending out warning information of poor contact between the head-mounted electroencephalogram signal acquisition component and the skin when any pressure value is lower than the set pressure threshold value, and sending out warning information of good contact between the head-mounted electroencephalogram signal acquisition component and the skin when all three pressure values are not lower than the set pressure threshold value.
4. A method for evaluating fatigue of a ship driver, characterized in that it is implemented by using the ship driver fatigue evaluation system according to claim 1, the method comprising the steps of:
s1, starting timing after starting work, controlling and receiving face images of a driver acquired by a camera at intervals of a fixed time period by the control module, carrying out identity recognition on the driver based on the face images, judging whether identity recognition information is changed in a first set time period from starting timing, repeatedly executing the step S1 with the change judging moment as a starting point when the change is judged, and entering the step S2 when the change is not judged;
s2, the control module simultaneously sends a signal acquisition instruction to the head-mounted electroencephalogram signal acquisition component and the intelligent bracelet by utilizing a third wireless communication module;
s3, the control module controls the speed sensor to detect the ship speed value and the signal acquisition time stamp in real time;
the control module controls the environmental noise sensor to detect the environmental noise value and the signal acquisition time stamp in real time;
the first micro controller respectively controls the left, middle and right side electroencephalograms to acquire left, middle and right side electroencephalograms and signal acquisition time stamps thereof in real time, and the signals are transmitted to the control module by utilizing the first wireless communication module and the third wireless communication module;
the second micro controller controls the pulse sensor to acquire pulse signals and signal acquisition time stamps thereof in real time, controls the temperature sensor to acquire wrist temperature signals and signal acquisition time stamps thereof in real time, and transmits the wrist temperature signals and the signal acquisition time stamps thereof to the control module by utilizing the second wireless communication module and the third wireless communication module;
s4, the control module judges whether the speed value is zero in the second set time period and whether the identity identification information is changed in the second set time period, when the speed value is zero, the step S4 is re-executed by taking the moment of the follow-up speed which is not zero as a starting point, when the identity identification information is changed, the step S1 is re-executed by taking the moment of the change as the starting point, and when the speed value is zero, the step S5 is entered;
s5, the control module performs preprocessing operation on the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals;
s6, the control module performs feature extraction on the preprocessed environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals to sequentially extract time domain features and frequency domain features of the environmental noise signals, the brain electrical signals, the pulse signals and the wrist temperature signals respectively;
s7, the control module respectively matches the time/frequency domain characteristics of the environmental noise signals, the average time/frequency domain characteristics of the electroencephalogram signals, the time/frequency domain characteristics of the pulse signals and the time/frequency domain characteristics of the wrist temperature signals with the awake range set and the fatigue range set to determine whether a driver is in an awake state or in a fatigue state, and when the driver is in the awake state, the next second set time period is entered to repeatedly execute the step S4, and when the driver is in the fatigue state, the step S8 is entered;
s8, the control module matches the time/frequency domain characteristics of the environmental noise signals, the average time/frequency domain characteristics of the electroencephalogram signals, the time/frequency domain characteristics of the pulse signals and the time/frequency domain characteristics of the wrist temperature signals with corresponding characteristics in each fatigue level, and determines the specific fatigue level of the driver;
step S7 includes the steps of: the control module is used for respectively matching the environmental noise signal time/frequency domain characteristic, the brain electrical signal average time/frequency domain characteristic, the pulse signal time/frequency domain characteristic and the wrist temperature signal time/frequency domain characteristic with the corresponding characteristic in the awake range set and the corresponding characteristic in the fatigue range set one by one, if the time/frequency domain characteristic value of a certain signal is positioned in the corresponding characteristic range in the awake range set or the fatigue range set, the awake range set or the fatigue range set is successfully matched once, the number of successful matching in each of the awake range set and the fatigue range set is counted, the number of successful matching in the awake range set and the number of successful matching in the fatigue range set are judged, if the corresponding number of the awake range set is larger than the corresponding number of the fatigue range set, the driver is judged to be in the awake state, then the next second set time period is entered for judgment, and if the corresponding number of the fatigue range set is larger than the corresponding number of the awake range set, the driver is judged to be in the fatigue state, and the specific fatigue level of the driver is further judged;
step S8 includes the steps of: the control module performs one-to-one matching on the environmental noise signal time/frequency domain feature, the electroencephalogram signal average time/frequency domain feature, the pulse signal time/frequency domain feature and the wrist temperature signal time/frequency domain feature with corresponding features in each fatigue level, if the time/frequency domain feature value of a certain signal is located in a corresponding feature range in a certain fatigue level, the fatigue level is successfully matched once, the number of successful matches in each fatigue level is counted, the fatigue level probability corresponding to the matching success set number range to which the number of successful matches belongs is queried, and the fatigue level probability with the largest numerical value is displayed, so that the specific fatigue level and the specific fatigue level probability of a driver are determined.
5. The ship driver fatigue evaluation method according to claim 4, wherein in step S5, the control module performs normalization processing on the environmental noise signal, each electroencephalogram signal, the pulse signal, and the wrist temperature signal, and performs noise reduction filtering processing on the environmental noise signal, each electroencephalogram signal, the pulse signal, and the wrist temperature signal after normalization processing.
6. The ship driver fatigue evaluation method according to claim 4, wherein the elastic binding belt is an adjustable elastic binding belt, pressure sensors are respectively arranged on the left, middle and right sides in the flexible shell, each pressure sensor detects the pressure between the corresponding side of the flexible shell and the forehead skin and transmits each pressure value to a first micro controller, and the first micro controller transmits each pressure value to a control module through a first wireless communication module and a third wireless communication module;
the control module judges whether any pressure value is lower than a set pressure threshold, sends out warning information of poor contact between the head-mounted electroencephalogram signal acquisition component and the skin when any pressure value is lower than the set pressure threshold, and sends out warning information of good contact between the head-mounted electroencephalogram signal acquisition component and the skin when all three pressure values are not lower than the set pressure threshold.
CN202310202258.9A 2023-03-06 2023-03-06 Ship driver fatigue evaluation system and method Active CN116035579B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310202258.9A CN116035579B (en) 2023-03-06 2023-03-06 Ship driver fatigue evaluation system and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310202258.9A CN116035579B (en) 2023-03-06 2023-03-06 Ship driver fatigue evaluation system and method

Publications (2)

Publication Number Publication Date
CN116035579A CN116035579A (en) 2023-05-02
CN116035579B true CN116035579B (en) 2023-08-25

Family

ID=86113525

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310202258.9A Active CN116035579B (en) 2023-03-06 2023-03-06 Ship driver fatigue evaluation system and method

Country Status (1)

Country Link
CN (1) CN116035579B (en)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108694814A (en) * 2018-07-11 2018-10-23 中国医学科学院生物医学工程研究所 Fatigue driving method for early warning, device, equipment and storage medium
CN109887239A (en) * 2019-03-16 2019-06-14 南京英诺微盛光学科技有限公司 It is a kind of for monitoring the wearable device and application method of fatigue driving
JP6784424B1 (en) * 2019-08-01 2020-11-11 肇▲慶▼学院 Overwork detection warning system and method based on machine vision
CN112401908A (en) * 2020-12-02 2021-02-26 中国人民解放军海军特色医学中心 Fatigue monitoring device, fatigue monitoring method, computing equipment and storage medium
CN113947869A (en) * 2021-10-18 2022-01-18 广州海事科技有限公司 Alarm method, system, computer equipment and medium based on ship driving state

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108694814A (en) * 2018-07-11 2018-10-23 中国医学科学院生物医学工程研究所 Fatigue driving method for early warning, device, equipment and storage medium
CN109887239A (en) * 2019-03-16 2019-06-14 南京英诺微盛光学科技有限公司 It is a kind of for monitoring the wearable device and application method of fatigue driving
JP6784424B1 (en) * 2019-08-01 2020-11-11 肇▲慶▼学院 Overwork detection warning system and method based on machine vision
CN112401908A (en) * 2020-12-02 2021-02-26 中国人民解放军海军特色医学中心 Fatigue monitoring device, fatigue monitoring method, computing equipment and storage medium
CN113947869A (en) * 2021-10-18 2022-01-18 广州海事科技有限公司 Alarm method, system, computer equipment and medium based on ship driving state

Also Published As

Publication number Publication date
CN116035579A (en) 2023-05-02

Similar Documents

Publication Publication Date Title
CN104183091B (en) System for adjusting sensitivity of fatigue driving early warning system in self-adaptive mode
CN101224113B (en) Method for monitoring vehicle drivers status and system thereof
CN106778618A (en) A kind of fatigue driving monitoring early warning system
CN105286802B (en) Driver Fatigue Detection based on video information
CN104146722A (en) Driving fatigue detecting and grading early warning device and method based on head signals
CN104240446A (en) Fatigue driving warning system on basis of human face recognition
CN105678959A (en) Monitoring and early-warning method and system for fatigue driving
CN104068868A (en) Method and device for monitoring driver fatigue on basis of machine vision
CN108937923A (en) A kind of real-time driving fatigue monitoring system based on EEG signals, electro-ocular signal and electromyography signal
CN109953763A (en) A kind of vehicle carried driving behavioral value early warning system and method based on deep learning
CN102930693A (en) Early warning system and method for safe driving
CN106467057A (en) The method of lane departure warning, apparatus and system
CN103700220A (en) Fatigue driving monitoring device
CN108021875A (en) A kind of vehicle driver's personalization fatigue monitoring and method for early warning
CN110427830A (en) Driver's abnormal driving real-time detection system for state and method
CN110287916A (en) It is a kind of for judging the method and system of driver attention
CN112220480A (en) Driver state detection system and vehicle based on millimeter wave radar and camera fusion
CN116035579B (en) Ship driver fatigue evaluation system and method
CN103824421B (en) Active safety fatigue driving detection caution system
EP3056375B1 (en) Sleepiness detecting device
CN104361759B (en) Signal lamp identification system and method
CN109383516A (en) A kind of anomaly analysis behavioral value system based on user behavior analysis
CN111724565A (en) Safe driving monitoring system
CN112208544A (en) Driving capability judgment method for driver, safe driving method and system thereof
CN108556629B (en) Driving safety auxiliary system and method

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
GR01 Patent grant
GR01 Patent grant