51 results about "Mental load" patented technology

The invention relates to a method and an electronic device for implementing the method for measuring mental load. The electronic device generates at least two different cognitively loading tasks for the person participating in the measurement, the first task determining a reference level and at least one other task determining the loading capacity level. The electronic device determines the pulse parameters of the person participating in the measurement during the cognitively loading tasks. The electronic device also compares the pulse parameters during the different tasks with each other. Finally, the electronic device generates a value descriptive of the mental load of the person participating in the measurement on the basis of the comparison of the pulse parameters.

The invention discloses an ultrasonic gait detection device and method. The method is characterized by comprising the following steps: installing an ultrasonic detection system in front of a walking aid robot platform, respectively detecting the distance between the left and right legs of the testee and the ultrasonic detection platform by multiple ultrasonic sensors, extracting gait information in the walking process of the human body, and analyzing and calculating gait parameters, including average step length, average pace, step frequency, instantaneous speed and the like. The device comprises an ultrasonic transceiver, a data acquisition and transmission device, a gait data processing unit and a gait characteristic parameter calculation and analysis unit. The detection device is installed on the walking aid robot platform, and no device is installed on the testee body, so that the ultrasonic gait detection device can detect the gait of the testee without any restriction, thereby reducing the mental load of the testee in the gait detection process; the extracted gait characteristic parameters are more accurate; and the detection system has the advantages of simple structure and low cost, and is convenient to use and install.

The invention discloses a self-help defecation bed for a bedridden patient, which comprises a bed body, wherein the top surface of the bed body is provided with a bed frame consisting of a longitudinal beam and a cross beam; the bed frame is paved with a bed board and a mattress; a side turning device is arranged between the bed frame and the bed board in the middle and head position of the bed body; the middle bed board and the mattress are provided with a defecation hole correspondingly; the downside of the bed body is provided with a defecation hole plug corresponding to the defecation hole; along the longitudinal beam in the middle bed body is correspondingly provided with a longitudinal slideway; the longitudinal slideway is provided with a feces receiving device sliding along the longitudinal slideway; the feces receiving device is provided with a feces receiving pan; the feces receiving device is linked with a motor arranged at the bottom of the bed through a driving mechanism; and an on-off mechanism is arranged between the defecation hole plug and the feces receiving device. The self-help defecation bed can allow the bedridden patient to relieve the bowels by self in case of no nursing, reduce the dependence on others and self mental load and help the patient to turn over, and can be popularized and applied at home, hospital and geracomium.

The invention discloses a mental load detection method. The method comprises the following steps of: extracting linear feature parameters and non-linear feature parameters of brain electric signals; extracting blood oxygen saturation degree indexes from brain near infrared spectrum signals, and taking the blood oxygen saturation degree indexes as blood oxygen saturation degree feature parameters; averaging the performance indexes of all sections of auxiliary task, acquiring the performance index of average auxiliary task, finding features sensitive to the performance index of average auxiliary task from the linear feature parameters, the non-linear feature parameters and the blood oxygen saturation degree index parameters, and acquiring sensitive features; establishing a mental load detection model according to the sensitive features and the performance index of the average auxiliary task by adopting a support vector regression or artificial neural network; and outputting mental load indexes through the mental load detection model, regulating the task of operators so that the mental load indexes are within the preset range, thus finishing the flow. The method implements the on-line detection of the mental load and expands the application range.

An information service system for a vehicle includes: an information obtaining element for obtaining information, which includes classification information for defining an importance level and an urgency level; a plurality of information output elements having various sensory types so that the information output elements inform the information of an user with various sensory types; a user load detector for detecting a physical and mental load of the user; a selector for selecting one or more information output elements according to the classification information; and a controller for controlling to output the information with the one or more information output elements. The selector selects the one or more information output elements based on the physical and mental load and a priority order of the information.

The invention discloses a mental load level recognition method. The mental load level recognition method includes: acquiring EEG signals through a plurality of electrodes, and recording reaction time parameters corresponding to the EEG signals; extracting EEG signal parameters from the acquired EEG signals; selecting a preset number of EEG signal parameters as a driving mental load feature index from the acquired EEG signal parameters; establishing an SVM recognition model on the basis of the driving mental load feature index; and recognizing the mental load level according to the SVM recognition model. The mental load level recognition method can achieve dynamic real-time recognition of the mental load level of a driver.

An information service system for a vehicle includes: an information obtaining element for obtaining information, which includes classification information for defining an importance level and an urgency level; a plurality of information output elements having various sensory types so that the information output elements inform the information of an user with various sensory types; a user load detector for detecting a physical and mental load of the user; a selector for selecting one or more information output elements according to the classification information; and a controller for controlling to output the information with the one or more information output elements. The selector selects the one or more information output elements based on the physical and mental load and a priority order of the information.

The invention relates to a method and an electronic device for implementing the method for measuring mental load. The electronic device generates at least two different cognitively loading tasks for the person participating in the measurement, the first task determining a reference level and at least one other task determining the loading capacity level. The electronic device determines the pulse parameters of the person participating in the measurement during the cognitively loading tasks. The electronic device also compares the pulse parameters during the different tasks with each other. Finally, the electronic device generates a value descriptive of the mental load of the person participating in the measurement on the basis of the comparison of the pulse parameters.

The invention provides a pilot mental load measurement system based on a flight simulator. The pilot mental load measurement system comprises a flying emergency setting subsystem (1) and a pilot mental load horizontal measurement subsystem (2). The flying emergency setting subsystem (1) is used for setting abnormal information in a cockpit in the flying process; the pilot mental load horizontal measurement subsystem (2) is used for measuring the pilot mental load grade under a flying emergency. The pilot mental load measurement system comprises three modules which are the pilot operation performance index measuring module, the pilot physiological parameter measuring module and the pilot mental load grade judging module. The pilot operation performance index measuring module is used for recording and analyzing the correct operation rate and the reaction time of a pilot to the abnormal information in the flying operation process. The pilot physiological parameter measuring module is used for recording and analyzing change situations of pilot physiological parameters (a heart rate variability index SDNN) in the flying operation process. The pilot mental load grade judging module is used for judging the mental load level of the pilot.

The invention provides a method for representing a mental load degree of a driver on a highland road. The method comprises the following steps: collecting heart rate index change of the driver, real-time position of a vehicle, real-time speed and altitude when the driver drives on the highland road; converting the heart rate index into heart-rate growth rate; dividing a road alignment and counting and recording a corresponding alignment index; performing multiple regression treatment on the heart-rate growth rate of the driver, the average elevation of the current road section, the alignment index of the current road section and the real-time speed of the driven vehicle, thereby acquiring a model; correspondingly substituting all the parameter values of the road section into the model, thereby acquiring the mental index of the driver; comparing the mental index with the heart-rate growth rate in an evaluation standard, thereby judging if the real-time mental load of the driver on the road section is within a safe level. According to the method provided by the invention, the problem of judging the mental load degree of the driver under an altitude environment can be solved and the accuracy of the practical application can be further increased.

The invention discloses an electroencephalogram evaluation system based on an electroencephalogram-based simulation aircraft. The system comprises a simulation flight simulation analysis system, a simulation piloting system and an electroencephalogram experiment system. The purpose of the invention is to study the driving experience of a pilot. Electroencephalogram technology and the flight simulation technology are used, and a set of simulated piloting platforms combining an electroencephalogram system is built. A tested person generates a series of electroencephalogram signals by operating asimulated piloting system and receiving feedback from the system, and the electroencephalogram signals are collected, displayed and recorded by an electroencephalogram experiment system. A simulationflight simulation analysis system processes and stores the electroencephalogram event data generated by the simulated piloting system and real-time stamps. After the flight test is finished, the tested person carries out mental load evaluation on each task, and then the mental load of the operator is analyzed in combination with the electroencephalogram data. The system platform provides a good experiment and training platform for researching the problems of pilot mental load and mental fatigue.

The embodiment of the invention provides a mental load detection method and device. The method comprises the following steps of: acquiring a physiological signal of a to-be-detected object; inputtingthe physiological signal into a preset time convolution network model, and obtaining a mental load type of the to-be-tested object according to an output result of the time convolution network model,wherein the physiological signal comprises an electroencephalogram signal, and the time convolution network model is obtained after training according to a physiological signal sample with a mental load type label. The physiological signals are input into the preset time convolution network model, so that the preset time convolution network model is obtained after training according to the physiological signal sample with the mental load type, and the recognition result of the mental load type can be output, so that the detection process is quick and accurate, the calculation consumption is lower, and meanwhile, the redundant information can be automatically eliminated by utilizing the time convolution network model.

During a driving activity of an automobile, a work characteristic evaluating apparatus is provided for judging a factor (a physical work load or a mental load) of stress that a work activity places on the worker to evaluate a work characteristic. The work characteristic evaluating apparatus 1 comprises a masseter muscle myoelectric potential acqusition device 10 which measures and acquires myoelectric potential of a masseter muscle which moves independently of the driving activity of the driver, a work intensity acquisition device 20 which measures and acquires steering torque around the steering shaft as a work intensity of steering activity, a correlation calculating module 38 which computes a correlation between time-series data of the myoelectric potential of the masseter muscle and time-series data of the steering torque, and a judgment module 39 which judges whether the stress placed on the worker is caused by a physical work load or a mental load based on the correlation coefficient.

The invention discloses a method for evaluating vehicle sound quality based on a pupil diameter, and belongs to the technical field of vehicle testing. The method for evaluating the vehicle sound quality based on the pupil diameter is provided aiming at solving the deficiencies that by using a sound quality subjective evaluation method, multi-sample comparison or grading can only be conducted and a specific ratio scale can not be given, and a lot of differences exist in evaluation index selecting of a sound quality objective evaluation method. The method comprises the steps of firstly selecting a sound quality evaluator, collecting a sample to be evaluated, and conducting the sound quality evaluation; then judging whether there is an illuminance-pupil diameter model of the selected evaluator, if there is no model, standard pupil diameter data is collected, and the illuminance-pupil diameter model is generated; if there is a model, the model is utilized to be subjected to sound quality quantization with the sound quality evaluation data. According to the method, a pupil diameter index of the mental load of the evaluator can be reflected through quantization, the deficiency of a ratio scale in the sound quality subjective evaluation method is made up, and the problem of differences of the sound quality objective evaluation index selecting is solved.

The invention discloses a vehicle-mounted device for detecting a driver workload based on image identification. The device comprises a collection unit, an image processing unit, a road alignment load level calculation unit, a visual load level calculation unit, a display unit and a storage unit, wherein the display unit is used for receiving data of the road alignment load level calculation unit and the visual load level calculation unit, displaying a comprehensive driving load of a road environment in real time after quantitative fusion, and displaying a running state of a system. According to the vehicle-mounted device for detecting the driver workload based on the image identification, the visual load of a driver and the mental load caused by road alignment are fused, and the comprehensive driving load of the driver is displayed and can be analyzed by a administrative department and a design department.

The present invention provides methods and systems for determining mental states of a user based on mental load index, comprising: analysing image data to identify feature(s) of at least one eye while presenting user with dynamic physiological-responsive stimuli; calculating, based on the identified feature(s), spatiotemporal fluctuations over time for the feature(s); calculating, based on the spatiotemporal fluctuations, spectral pattern(s) having a first and second frequency; calculating mental load pattern(s) by bounding ratio between the spectral patterns for the first and second frequencies in time interval(s) corresponding to stimuli level changes; identifying correlation between each mental load pattern(s) and the stimuli level in the time interval(s); and determining, based on the correlation, a mental load index comprising time interval(s) corresponding to a plurality of mental states identified by comparing each mental load pattern(s) to a threshold; and classifying mental state(s) based on the mental load index in each time interval(s).

The invention discloses a mental load detection method and system and related equipment. The method comprises the steps: after it is detected that a subject completes a preset test task, measuring thebrain of the subject through electroencephalogram test equipment, and acquiring electroencephalogram signals in M channels through the electroencephalogram test equipment; measuring the forehead areaof the subject through a functional near infrared spectrum to obtain a functional near infrared spectrum signal of the forehead area; processing the electroencephalogram signal of each channel to obtain a first characteristic parameter of the electroencephalogram signal in each channel; processing the functional near infrared spectrum signal to obtain a second characteristic parameter of the functional near infrared spectrum signal; and determining the mental load level of the subject for the mental load level according to the first characteristic parameter of the electroencephalogram signalin each channel and the second characteristic parameter of the functional near infrared spectrum signal. According to the method, online detection of mental loads is achieved, and detection of the mental loads is more accurate.

The invention relates to a mental workload assessment method, device, equipment and medium. The method comprises the steps of firstly obtaining an electroencephalogram signal and an electrocardiosignal of a testee, then carrying out the feature extraction of the electroencephalogram signal to obtain a PSD feature, carrying out the feature extraction of the electrocardiosignal to obtain an HR feature and an HRV feature, and finally taking the electroencephalogram signal, the PSD feature, the HR feature and the HRV feature as model input, acquiring the mental load category of the testee by using the assessment model, so that the mental load category of the testee can be evaluated by integrating the electroencephalogram signal and the electrocardiosignal, and the evaluation precision can be remarkably improved.

The invention discloses a miner mental load evaluation method based on brain electrical detection. The evaluation method comprises steps of performing a continuous operation test for a miner and dividing an N-back task into a memory part and a judgment part; arranging the memory part before a CPT task, and the judgment part after the CPT task; taking the whole N-back task as a disturbing variable for increasing brain load on the to-be-tested miner; selecting 58 channel brain electrical data from data acquired by a Neurone 64 guiding system so as to analyze brain electrical characteristics of the miner with brain load; filtering the acquired brain electrical data via the genetic algorithm; and analyzing the brain load of the miner by use of the filtered brain electrical data. According to the invention, by controlling the brain load of a miner, pressure in the work of a miner is reduced; behavior errors of the workers are reduced; unsafe acts of the miner are reduced and avoided; accidents of coal mine enterprises are prevented; accident rate of human factors is reduced; and the evaluation method has important practical significance for management level of coal mine safety production in China.

A mental load cannot be appropriately evaluated when a tremor is detected by wearing an acceleration sensor on an arm and the like of a test subject; therefore, a tremor detector according to an exemplary aspect of the present invention includes pressure distribution detecting means for detecting pressures on a plurality of places in a plane and generating pressure information of information on pressure distribution in the plane; feature quantity extracting means for extracting a feature quantity from the pressure information; and tremor feature quantity extracting means for extracting a tremor-frequency feature quantity that is a frequency component of the feature quantity and includes a frequency component corresponding to a physiological tremor.

The invention discloses a mental load detection method. The method comprises the following steps of: extracting linear feature parameters and non-linear feature parameters of brain electric signals; extracting blood oxygen saturation degree indexes from brain near infrared spectrum signals, and taking the blood oxygen saturation degree indexes as blood oxygen saturation degree feature parameters; averaging the performance indexes of all sections of auxiliary task, acquiring the performance index of average auxiliary task, finding features sensitive to the performance index of average auxiliary task from the linear feature parameters, the non-linear feature parameters and the blood oxygen saturation degree index parameters, and acquiring sensitive features; establishing a mental load detection model according to the sensitive features and the performance index of the average auxiliary task by adopting a support vector regression or artificial neural network; and outputting mental load indexes through the mental load detection model, regulating the task of operators so that the mental load indexes are within the preset range, thus finishing the flow. The method implements the on-line detection of the mental load and expands the application range.

A traditional Chinese medicine for curing the mental burden bed-wetting belongs to a traditional Chinese medicine for curing bed-wetting. The components include: 9g of common yam rhizome, 9g of ootheca mantidis, 6g of cassia bark, 6g of combined spicebush root, 6g of sharpleaf galangal fruit, 3g of medulla tetrapanacis and 6g of dodder seed; the auxiliary prescription includes: for the patients with much sweat, 8g of fuxiaomai and 8g of largehead atractylodes rhizome are added; for the patients with loose stool, 6g of rhizoma zingberis; for the patients with red eyes, 10g of chrysanthemum and 10g of spicaprunellae are added; for the patients with sleepiness, 9g of thinleaf milkwort root and 9g of bhizoma acori calami are added. The substances in the prescription are made from natural traditional Chinese medicine plus traditional preparing methods. The materials are easy to collect, the prescription and the preparation methods are simple, and the cost of medicine preparation is low. The compatibility of the traditional Chinese medicine is simple; the medicine used in the prescription is fully natural herbal medicine, which is easy to collect and use; the preparation method is simple; the effects for taking and curing are good; the cost of the medicine is low, and the medicine is in particular suitable for the people living in remote villages far from towns; the cost is low for curing the people suffering from the mental burden bed-wetting, which solves the problem that the local area lacks medical conditions to cure the disease because of low household income and poor living condition.

The invention discloses an automatic mental load identification method and system. The automatic mental load identification method comprises the following steps of acquiring an electroencephalogram signal; carrying out separating on the electroencephalogram signal by adopting an independent component analysis method to obtain a plurality of independent electroencephalogram components; extracting energy features of each independent electroencephalogram component; and inputting the energy features into an SVM classifier to obtain a mental load classification result of the electroencephalogram signal. According to the automatic mental load identification method and system, the identification accuracy of mental load can be improved.

The invention relates to a method for adjusting the working items of a passenger in a movable bin. The method for adjusting the working items of the passenger in the movable bin comprises the steps that firstly, a passenger task-network model based on execution channels is established, wherein the task-network model is used for forming a relevant network graph on the execution channels according to the time and execution logic for tasks of the passenger; secondly, the working parameters of a system model are determined, wherein the working parameters include the time parameters and the resource parameters, the time parameters include the response time of the passenger and the movement time of the passenger, and the resource parameters are used for representing the mental load values of the passenger and the probability distribution of the mental load values of the passenger; thirdly, the mental load average value of the execution channels of the passenger is obtained through calculation according to the passenger task-network model determined in the first step and the working parameters determined in the second step; fourthly, the overall mental load of the passenger is obtained through calculation; fifthly, the sequence of the working items of the passenger is adjusted according to the overall metal load of the passenger, so that misoperation caused by a mental overload is avoided.

The invention discloses an intelligent management system for step-by-step settlement of recursively racking plates in a campus canteen, and the structure of the system comprises a man-machine interface station, an observation window, a microwave recursive rack, a hand-pull catching groove, an electronic bearing seat, a digital display tube and a buffer base. The intelligent management system provided by the invention realizes the effect of forming weighting step-by-step recursively rising settlement and meal-taking through the cooperation of the man-machine interface station and the microwaverecursive rack, realizes data feedback accurate settlement, reduces works with mental load and prolonged physical exertion, ensures people's rest time and settlement comfort by humanized substitutionof intelligent equipment, realizes the effect of simultaneously placing five or six plates in the front of the queue on the traying bracket for the students to provide a break time for the students who holds the plates for a long time. At the same time, since the chilled meals can be microwaved within the rack for output, the students can rest their arm muscles to maintain the tendon of the biceps, and healthy diet of hot meals is provided for the students after the settlement to promote the development.

The invention relates to a visual task mental load quantitative evaluation method and system. The method comprises the steps: firstly constructing an information structure diagram of each task sub-interface on an information display and control task interface based on a given information display and control task interface, and calculating the information complexity of each task sub-interface according to the information structure diagram of each task sub-interface based on the Shannon theorem; then calculating the visual task demand load and the visual personnel working capability of each task according to the information complexity, and calculating the mental load and the maximum residual mental load of the tester for completing each task by utilizing the visual task demand load and the visual personnel working capability; and finally, according to the mental load and the maximum residual mental load, processing and quantifying the mental load occupancy rate of each task of the tester in the task process, thereby realizing real-time and quantitative evaluation of the mental load.

The embodiment of the invention provides a mental load evaluation system and method. The system comprises an operator information module, an evaluation content management module, a test module, an evaluation report output module and a data management module, the operator information module can configure roles and permissions of users according to needs, and a plurality of subjective self-evaluation tasks, a plurality of objective evaluation tasks and a plurality of custom templates are configured in the test module, so that evaluation contents can be formed through free combination. The system and the method can adapt to personnel structures in different operation fields, improves the user experience, can combine subjective self-evaluation and objective evaluation tasks, can comprehensively evaluate the mental load of operators and can serve as an important evaluation index for the performance level of individual operation or team cooperation tasks, and the informatization of a man-machine interaction interface and the man-machine matching degree can be comprehensively reflected.

An object of the present invention is to disclose a method for configuring a critical safety function state tree of a nuclear power plant based on a visual model, compared with the prior art, Visual basic logic module is used to build the required state tree of key security functions. After you create the critical security feature status tree, the ability to store relevant state tree information in an encrypted format, Users only need to understand the functionality of the basic functional modules of visualization. According to the requirements, the required key safety function state tree canbe built and loaded into the system, thereby facilitating the development and confidentiality work, simplifying the development and maintenance work of the key safety function state tree, lightening the mental load of the configuration engineer, avoiding human error, improving the development efficiency, and realizing the purpose of the invention.

The invention discloses a multi-physiological parameter mental load prediction method and device, and the method comprises the steps: obtaining objective quantity data and subjective quantity data of an operator based on standard experiment tasks with different difficulties; performing data processing on the objective quantity data and the subjective quantity data of the operator to obtain training data; inputting the training data into a plurality of ensemble learning prediction models, and performing voting classification according to prediction results of different ensemble learning prediction models to obtain an optimal ensemble learning model; and performing real-time prediction on the mental load of the operator based on the optimal integrated learning model. By adopting the method and the device in the technical scheme, the mental load of the operator during working can be predicted in real time.