124 results about "Alertness" patented technology

Systems, devices and methods are provided for stimulating one or more nerves within a user. A system comprises stimulator having an electrode configured for contacting the outer skin surface at a target location and an energy source coupled to the stimulator, The energy source is configured to generate at least one electrical impulse and to transmit the electrical impulse transcutaneously from the electrode through the outer skin surface of the user to a selected nerve in the user. In certain aspects, the systems and methods are particularly useful for non-medical purposes, such as reducing stress and anxiety, enhancing relaxation, improving sleep, energy, concentration and mood, increasing mental or physical performance, promoting mental health, recovery and wellness, generally improving the health and wellbeing of a user and / or for temporarily or permanently improving intelligence, learning capacity, memory retention, recall, mood, alertness and / or sleep efficiency in human beings.

A driver or occupant health and alert monitoring and assistance system and associated techniques or methods include, among other features, monitoring vital signs of the driver and when these vital signs are determined to be outside of a predetermined range or pattern, alerting the driver via an infotainment system of a potential abnormal health condition and requesting a response from the driver regarding the same. Should the driver not respond within a predetermined period of time, the techniques further provide for taking emergency corrective action including autonomously slowing down the vehicle to a stop, alerting the emergency 911 system of the driver's situation, and / or alerting predetermined emergency contacts of the driver's potential abnormal health condition and vehicle state.

An embodiment related to a system, wherein the system comprising an alertness detector unit configured to detect an alertness signal of an occupant an alertness determination unit configured to determine an alertness of the occupant based on the alertness signal, an environment sensing unit configured to sense external data in a route, an analysis unit configured to analyze the external data to determine an external condition, a risk assessment unit configured to determine a risk level in real-time based on an analysis of the external data and the alertness of the occupant, and a control unit configured to adjust a seat if determined that the real-time risk level was above a threshold.

The invention discloses a multi-modal fusion alertness assessment method and system based on cross attention, and the method comprises the steps: carrying out the preprocessing of an original electroencephalogram signal of a user, and extracting a time-frequency domain-space feature # imgabs0 #; using a depth separable convolution module and an LSTM module to extract an electroencephalogram modal time dependency relationship feature # imgabs2 from the time-frequency domain-space feature # imgabs1 # in sequence; the method comprises the following steps: preprocessing an original electro-oculogram signal of a user to extract an eye movement feature # imgabs3 #, and obtaining an eye movement modal internal relation feature # imgabs5 # from the eye movement feature # imgabs4 # by using an outer product module and a CNN module in sequence; and performing multi-modal fusion on the electroencephalogram modal time dependency relationship characteristic # imgabs6 # and the eye movement modal internal relationship characteristic # imgabs7 # based on cross attention to obtain a fusion characteristic # imgabs8 #, and performing regression to obtain an alertness prediction result # imgabs9 # of the user. According to the method, intra-modal feature extraction and multi-modal feature fusion are respectively carried out on different information sources, so that the robustness and generalization of the features are improved, and the accuracy of alertness assessment is improved.

The invention discloses a real-time fatigue monitoring system based on an EEG signal, and relates to the technical field of neural regulation and control, and the system comprises a chaos reconstruction module which collects an original EEG signal, carries out the phase-space reconstruction of the original EEG signal through a chaos attractor processor, generates a chaos trajectory tensor, and carries out the phase-space reconstruction of the original EEG signal when the Lyapunov index of the chaos trajectory tensor exceeds a preset index threshold value, outputting a low-speed frequency band oscillation component and a high-speed frequency band oscillation component; and the closed-loop termination module is used for terminating the physical light field projection when the continuous detection periods of the updated alertness drop probability value, cognitive overload probability value and physiological fatigue probability value are all lower than a preset safety threshold value. Through multi-scale recursion phase space reconstruction, an original EEG signal is mapped to a three-dimensional chaotic trajectory tensor space, and dynamic frequency band decoupling is triggered by using a Lyapunov exponent threshold.

Apparatuses, systems, and methods for multiple types of alert along an alert bus. A memory device may detect multiple types of alert and use an alert signal along an alert bus to signal a controller of these alerts. Different pulse widths of the alert signal may be used to indicate the type of alert. For example if the alert signal is at an active level between a first duration and a second duration, it may indicate a first type of alert, if the alert signal is active between a third duration and a fourth duration, it may indicate a second type of alert. If the alert signal remains active for longer than a threshold amount of time, it may indicate a third type of alert.

The invention discloses an intelligent driving fatigue evaluation method and system, and relates to the technical field of automobile safety, and the method comprises the steps: obtaining the physiological data of a driver in a driving scene; the physiological data comprises myoelectricity data, heart rate data and respiratory rate data; calculating a driving fatigue evaluation index according to the physiological data; the driving fatigue evaluation indexes comprise physical load, alertness and cognitive load; and according to the driving fatigue evaluation index, calculating a fatigue driving comprehensive evaluation index by adopting a weight method. According to the method, psychological fatigue and physiological fatigue are comprehensively considered, and from three dimensions of physical load, alertness and cognitive load, indexes such as an electromyographic signal root-mean-square value, an electromyographic signal integral value, a heart rate mean value, a root-mean-square value of a whole-course adjacent NN interval difference, a ratio of heart rate variability low-frequency power to heart rate variability high-frequency power and heart rate breathing cross consistency are synthesized; the driving fatigue evaluation is carried out by adopting a weight method, so that the accuracy and objectivity of the driving fatigue evaluation can be effectively improved.

Methods, systems, and devices for providing physiological state-related insights associated with a user are described. A method includes receiving physiological data associated with the user from at least one wearable device, the physiological baseline providing reference user alertness data. The method further includes obtaining a physiological baseline associated with the user based at least in part on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data. The method further includes receiving additional physiological data associated with the user from the at least one wearable device. The method further includes obtaining current user alertness data based at least in part on the additional physiological data associated with the user. The method further includes identifying a trigger condition for providing a physiological state-related insight associated with the user relating to a traveling event involving at least one vehicle based at least in part on a comparison between the current user alertness data and the reference user alertness data. The method further includes causing a user device to provide the physiological state-related insight associated with the user.

The invention provides a cognitive function evaluation method based on neurovascular coupling analysis. The method comprises a signal preprocessing step, a signal processing step, a feature extraction step and a coupling coefficient calculation step. A new normal form of cognitive evaluation is constructed from nerve-blood vessel coupling and cross-system cooperation dimensions, and accurate description of a cognitive state is realized through real-time quantification of a dynamic cooperation effect of brain nerve activity (EEG) and blood flow regulation (CBP variability) and establishment of an association relationship between a dynamic cooperation index and cognitive ability (alertness, reaction speed and memory). And a new objective basis is provided for the fields of plateau medicine, intelligent health, neurological and mental disease diagnosis and treatment and the like.

The invention discloses a driver alertness prediction method based on electroencephalogram signals and a related device, and relates to the technical field of alertness prediction.The method comprises the steps that a time-space cross multi-head attention module is designed, and the time-space cross multi-head attention module comprises an Input Embedding module, an Inception module, a first summation module, a second summation module and a time-space fusion module; after electroencephalogram signal data in the driving process of a driver is obtained, feature extraction is conducted on the electroencephalogram signal data, electroencephalogram signal features are obtained, the electroencephalogram signal features comprise space-time fusion features, and the space-time fusion features are features obtained by conducting feature extraction on the electroencephalogram signal data through a space-time cross multi-head attention module; subsequently, the electroencephalogram signal features serve as input, and the alertness of the driver in the driving process is determined through the trained alertness prediction model. The method can improve the accuracy of predicting the alertness of the driver.

The invention discloses a safety supervision method and system for Internet rehabilitation nursing, and relates to the technical field of Internet medical treatment, and the method comprises the steps: building a dynamic space-time causal graph model based on collected data, defining a propagation path between nodes according to a biomechanical causal chain, and limiting a feature propagation time sequence through a causal time sequence verification layer; dynamically generating a gradient mask matrix based on the physiological rhythm represented by the heart rate variability data, and adjusting the gradient weight of the reinforcement learning strategy network by using the gradient mask matrix; in combination with electroencephalogram alertness wave signals and equipment torque parameters, performing cross-modal anomaly collaborative judgment through the adjusted reinforcement learning strategy network by utilizing a manifold envelope dynamic contraction mechanism; if it is judged that the cross-modal abnormity occurs, a dynamic safety threshold value is generated based on the electromyographic signals and patient individualized parameters, and switching of control modes of the rehabilitation equipment is driven according to the dynamic safety threshold value.

The invention provides an automatic safe driving cross-scene alertness detection method and device based on EEG analysis, and relates to the technical field of intelligent driving. The embodiment of the invention provides an automatic safe driving cross-scene alertness detection method based on EEG analysis, and the method solves the problem that the number of channels among different EEG devices is inconsistent by utilizing the capability of reconstructing the EEG information of a plurality of real channels of a pre-trained alertness detection network. The alertness detection network after fine tuning can reconstruct missing EEG information according to input EEG information of a small number of channels and corresponding brain region information, and a classification task is completed based on the reconstructed information.

The invention discloses a system for evaluating the cognitive function of a subject based on fNIRS and an interaction method. The head cap and the near-infrared light emitting / receiving probe in the system enable the imaging range to cover the frontal lobe, the temporal lobe and the occipital lobe; the cognitive assessment normal form interaction device sequentially executes a suppression control assessment normal form, an alert attention assessment normal form, a selection attention assessment normal form, a core attention network assessment normal form, a work memory assessment normal form and a cognitive control assessment normal form in a single block mode according to an execution sequence from simple to difficult; the signal acquisition device cooperatively acquires near-infrared brain function imaging time sequence data in the sequential execution process of each evaluation normal form; the processing device evaluates the cognitive function of the subject on the basis of the near-infrared brain function imaging time series data and behavioral data generated on the basis of the evaluation normal form. According to the method, the brain function data of more dimensions associated with the cognitive function can be acquired in a short time, and multi-angle evaluation and analysis on the cognitive function of the subject can be conveniently and clinically performed based on the fNIRS.

The present disclosure relates to methods and system for acquiring and analyzing biosignals or physiological signals of a person sitting in a vehicle and predicting (in real-time) time-varying attention, engagement level or alertness level using the biosignals. The biosignals may be acquired using one or more clusters of electrodes together with a wearable user device or from a sensing device that is embedded in the seat of the vehicle. In some embodiments, the biosignals may be utilized to predict restedness level of the subject, to monitor or predict physiological state of the subject, to detect a distress situation and to adapt a vehicle control accordingly. In some other embodiments, the biosignals can be transformed into communication, for example, speech signals or instructions for the vehicle. One or more actions may be triggered based on the analysis of the biosignals including engaging the person, generating alerts, or adapting the vehicle control.

Methods, systems, and devices for providing physiological state-related insights associated with a user are described. A method includes receiving physiological data associated with the user from at least one wearable device, the physiological baseline providing reference user alertness data. The method further includes obtaining a physiological baseline associated with the user based at least in part on the baseline physiological data associated with the user, the physiological baseline providing reference user alertness data. The method further includes receiving additional physiological data associated with the user from the at least one wearable device. The method further includes obtaining current user alertness data based at least in part on the additional physiological data associated with the user. The method further includes identifying a trigger condition for providing a physiological state-related insight associated with the user relating to a traveling event involving at least one vehicle based at least in part on a comparison between the current user alertness data and the reference user alertness data. The method further includes causing a user device to provide the physiological state-related insight associated with the user.

A device relating to a floater for use by a non-swimmer for buoyancy comprising a floating flatbed with coded descriptions (lateral ends: front end 14, back end 12) and a plurality of paired straps with buckles (20,22) to secure the floater flatbed (10) fixed in the swimmer’s body. This is designed to keep the non-swimmer afloat while concentrating on their hand and leg exercises. The floating flatbed is wrapped either at the upper limbs posterior or anterior portion of the body; a webbing belt with safety mechanisms buckled around the body which can be fixed at the levels; waist, abdominal, and upper back (posterior) or chest part (anterior). An adjustable strap is buckled across shoulders (24, 26) to fasten the device in place below the jaw with a plane surface of a floater which allows use purposely for either supine or prone floating mechanics fundamental in learning the basic skills for any appropriate floating position. Apparently, problems like drowning and other water accidents happen in just any part of the globe usually caused by panic and water anxiety. The device contains characteristics easy for use by non-swimmers at any age level for water safety and training device for non-swimmers particularly those who manifest water anxiety. Acquired skill in floating somehow creates mental alertness as a greater opportunity for survival during atrocities.

The invention relates to a daytime short-term sleep evaluation method based on multi-dimensional lighting factors, and belongs to the technical field of sleep monitoring. The method comprises the following steps: obtaining individual characteristics, afternoon nap behavior characteristics and a sleep quality evaluation result of a research object, and carrying out code conversion to obtain a correlation analysis result of the afternoon nap characteristics and an afternoon nap light environment; setting a physiological rhythm test according to a correlation analysis result, and performing a light intervention experiment on the research object through the physiological rhythm test to obtain experimental effect data; staged regression analysis is carried out on test indexes in experimental effect data along with non-visual effect illumination changes by establishing an illumination adjustment model based on the afternoon nap rhythm and moment, and a health rhythm illumination parameter standard table is established according to a staged regression analysis result. Sleep quality is effectively optimized according to a health rhythm illumination parameter standard table, emotion and alertness are adjusted, and sleep disorders are reduced.

The present disclosure relates to non-therapeutic uses of compounds or combinations thereof to increase cognitive performance, alertness and / or energy levels of a human or animal, as well as an oral product comprising said compounds or combinations thereof.

The present application discloses a system and interactive method for evaluating the cognitive function of a subject based on fNIRS. The head cap and near-infrared light emitting / receiving probe in the system enable the imaging range to cover the frontal lobe, temporal lobe, and occipital lobe; the cognitive assessment paradigm interactive device sequentially executes the inhibitory control assessment paradigm, the alert attention assessment paradigm, the selective attention assessment paradigm, the core attention network assessment paradigm, the working memory assessment paradigm, and the cognitive control assessment paradigm in a single-block mode in an order of execution from simple to difficult; the signal acquisition device collaboratively collects near-infrared brain function imaging time series data during the sequential execution of each assessment paradigm; the processing device evaluates the cognitive function of the subject based on the near-infrared brain function imaging time series data and the behavioral data generated based on the assessment paradigm. The present application can obtain brain function data of more dimensions associated with cognitive function in a relatively short period of time, which is convenient for clinical evaluation and analysis of the cognitive function of the subject from multiple angles based on fNIRS.

In an illustrative embodiment, systems and methods for treating stress and / or for improving alertness in a subject using neurostimulation therapy include placing first electrode(s) on, over, or adjacent to an auricular branch of the vagus nerve, placing second electrode(s) on, over or adjacent to an auriculotemporal nerve, and delivering therapeutic stimulation pulses via the first electrode(s) and the second electrode(s) by delivering a first series of stimulation pulses to the first electrode(s), the first series configured to increase activity in neural medullary structure(s), and delivering a second series of stimulation pulses to the second electrode(s), the second series configured to increase activity in neural structures within the Trigeminocervical Complex.

An alertness detection device according to the present invention includes an alertness acquisition unit (131) that acquires alertness of a driver calculated from a facial image including a face of the driver of a vehicle, a viewing direction acquisition unit (132) that acquires a viewing direction including a line-of-sight direction or a facial direction of the driver calculated from the facial image, a vicinity information acquisition unit (133) that acquires vicinity information indicating a situation in a vicinity from a vicinity detection device that detects the situation in the vicinity of the vehicle, an attention level estimation unit (134) that estimates an attention level of the driver in the situation in the vicinity on the basis of the viewing direction that is acquired and the vicinity information that is acquired, and a correction unit (135) that calculates a corrected alertness by correcting the alertness that is acquired using the attention level that is estimated, and outputs the corrected alertness that is calculated.

The present invention discloses a low-cost and student-oriented solution for enhancing posture and combating drowsiness during long study periods. With simplicity and usability in mind, the system is integrated into a standard study chair with ease and utilizes low-cost electronic devices like pressure sensors (2), a tilt sensor (3), and a vibration motor (4) to establish a smart feedback system promoting correct posture and vigilance. The system works by constantly observing the seating activity of the user. Pressure sensors (2) embedded within the seat and backrest measure the presence and posture of the user, while a tilt sensor (3) built into the headrest monitors forward head movement, which is an early indication of drowsiness or distraction. Whenever the system perceives slouching, extended inactivity, or excessive head nodding over a predefined threshold angle, it initiates a subtle vibration motor (4) integrated into the chair. Unlike wearable solutions that may be uncomfortable or intrusive, the chair-based system provides a non-invasive experience. It does not intrude into the user's space but rather integrates smoothly into their surroundings without the need for them to wear a device or alter their usual study habits. Basic sensors and a microcontroller making the design low cost and easy to build make it suitable for students, teachers, or hobbyists looking for health-oriented innovations. Further, this intelligent study chair (1) can be modified for purposes of usage in schools, libraries, coaching institutions, or even home study rooms. By dealing with both posture and sleepiness within an integrated system, not only does it enhance physical health but also mental concentration. Overall, this project describes a new yet practical methodology for enhancing study habits through intelligent furniture design providing comfort and productivity in an intelligent, easy-to-use configuration.

The invention provides a method for identifying subject decision confidence through a decision self-confidence data acquisition normal form. The method comprises the steps of decision self-confidence data acquisition and alertness data acquisition. The decision-making self-confidence degree data acquisition is characterized in that electroencephalogram and eye movement data of three decision-making self-confidence degrees of a subject are acquired through three sub-experiments; the alertness data acquisition comprises the step of acquiring electroencephalogram and eye movement data of the alertness of a subject in an interval time period of acquiring decision self-confidence degree data; the alertness acquisition part is used for acquiring electroencephalogram and eye movement data of a subject before a mark appears as alertness data of the subject by using the mark appearing at a random interval time; and finally, performing multi-modal decision fusion, namely performing preprocessing, feature extraction and classification processing on the data of the electroencephalogram mode and the eye movement mode, and synthesizing final classification results to obtain a decision confidence recognition result.

This invention discloses a method for assessing sleep quality based on multimodal features in a waking state, comprising: S1, guiding subjects to complete a sleep quality scale, collecting pulse wave signals, facial thermal images, and corresponding temperature matrices of subjects in a resting state, and conducting a psychological alertness task test; S2, extracting heart rate, heart rate variability, and pulse wave morphology features from the pulse wave signals; S3, identifying key points on the face, determining regions of interest, and extracting facial temperature features; S4, analyzing the acquired psychological alertness task test data, statistically analyzing and extracting reaction time and attention maintenance-related indicators; S5, constructing a training dataset; S6, using the training dataset to train a classifier and construct a sleep quality classification model; S7, inputting the multimodal features collected from new users in a waking state into the sleep quality classification model and outputting the assessment results. This invention provides a method for assessing sleep quality in a daytime waking state.

The present invention discloses an emotional state and neuroelectrophysiological state regulating device, verification system and method, which belongs to the field of physical state regulation, and includes: a voltage generating module, which is used to output an extremely low frequency high voltage; a radiation module, which is used to convert the high voltage into an electric field, so that the subject is in the electric field, and then regulates the subject's subjective emotions, physiological reactions, neural electrical activities, etc. After the electric field intervention, the subject showed a lower level of cerebral cortex arousal, which was manifested as an increase in the power spectrum density of α and θ frequencies, and a significant decrease in subjective emotions related to exploration motivation and alertness, indicating that the subject was in a more relaxed state after acute stress; the extremely low frequency high voltage electric field can promote emotional regulation, and the overall negative emotion score of the subjects after the intervention is lower, and the anxiety level is also significantly reduced. The heart rate and blood pressure levels of the subjects after the electric field intervention are reduced, and both subjective and physiological indicators reflect that the physical and mental state of the subjects after the electric field intervention is relatively more stable.

A system and method for determining a user's daytime alertness is disclosed. The system may include at least one sensor sensing a user's physical phenomenon and a computer system. The computer system may receive sensor readings of the user from the sensor during a sleep session, provide the sensor readings as inputs to a model trained to predict the user's alertness level based on the user's physical phenomenon and / or historical data relating to the user and / or a user population, receive as output from the model data indicative of a predicted alertness level of the user for a period of time, determine action suggestions for the user based on the predicted alertness level for the period of time, and generate an output to the user presented on a graphical user interface display including at least one of (i) the predicted alertness level and (ii) the action suggestions.

The invention provides an information provision system, an information provision method, and a computer program product, which can suppress the occurrence of excessive alert and insufficient alert when a user riding on a moving body is alerted through an HMI using an intelligent agent. An information provision system (1) is provided with: a user state recognition unit (11) that recognizes the state of a user (U) riding on a moving body (100); a user emotion estimation unit (12) that estimates the emotion level of the user (U) from a prescribed index value on the basis of the recognition result of the state of the user (U); and a smart agent control unit (13) that provides the user (U) with an HMI that uses a personified smart agent and performs voice output in a pattern corresponding to an emotion level based on a prescribed index value of the smart agent. When the emotion level of the user (U) estimated by the user emotion estimation unit (12) is within a predetermined determination range, the smart agent control unit (13) controls the emotion level of the smart agent to a target level for changing the emotion level of the user (U) outside the determination range.

A method for estimating alertness of a human body is provided. The method comprises the following steps: acquiring a bio-electricity signal of a human body; based on the bio-electricity signal, obtaining characteristic data of the bio-electricity signal for estimating the alertness of the human body; and estimating the alertness value of the human body by using a regression neural network based on the feature data of the bio-electricity signal.

The application relates to a method and system for determining the front distance of a work zone warning sign, the method comprising: obtaining eye movement and electroencephalogram test data, processing the eye movement and electroencephalogram test data; establishing a matter element comprehensive evaluation model, inputting the processed eye movement and electroencephalogram test data into the matter element comprehensive evaluation model, and obtaining an evaluation grade and a corresponding characteristic value; and determining the front distance of the work zone warning sign according to the evaluation grade and the corresponding characteristic value. The method determines the effective front distance range of the work zone warning sign from the perspective of the change of the driver's alertness, constructs a comprehensive evaluation model based on matter element analysis to determine the time for maintaining the driver's alertness, and thus obtains the reasonable front distance of the work zone warning sign, which is helpful for the reasonable setting of the work zone warning sign.