30 results about "Alertness" patented technology

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.

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.

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 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.

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.

The present invention relates to a composition for inhalation, and more particularly, to a composition for inhalation, the composition for inhalation for enhancing alertness and vigor according to an embodiment comprising: caffeine; and a reinforcing agent comprising one or more elements selected from the group consisting of glucose and magnesium.

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.

This disclosure provides compositions and methods for improving human cognitive function, mood, and / or arousal. In one embodiment, the method comprises administering an edible composition to a person in need of improvement in condition, the composition comprising a combination of gamma-aminobutyric acid and caffeine. The edible composition has a weight ratio of total gamma-aminobutyric acid to total caffeine of about 1:50 to about 10:1.

The invention discloses a body and mind state assessment method and system based on multi-mode biological signal fusion processing. According to the method, human face and body features are collected through videos, and features such as micro-expressions, eye movements (pupils and gazes), breathing modes, postures and physiological micro-movements are extracted; generating a multi-dimensional state vector by adopting timestamp registration and a cross-modal attention and gating fusion network in combination with an individual baseline and adaptive calibration, and outputting indexes including emotion, pressure, alertness and the like and a confidence interval; and triggering a prompt or intervention suggestion when the preset threshold value is exceeded. The system supports edge end quantitative operation, and data security is guaranteed through federated learning and privacy protection technologies. The method has remarkable effects in the aspects of anti-noise robustness, individualized adaptation and credibility, and is suitable for robots and man-machine interaction scenes.

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

Contemplated compositions and methods employ betalains for treatment of various conditions, and especially osteoarthritis, sinusitis, contact dermatitis, acne, an allergic condition, reduced mental alertness, reduced physical strength, reduced physical endurance, and / or impaired mood.

The invention discloses a psychological intervention method of a wearable relaxation device, the wearable relaxation device comprises a wearable waistcoat and a headgear, the front and back of the wearable waistcoat are both provided with a heating sheet and an air bag, and the headgear is internally provided with an ultrasonic generator; a user wears the head sleeve on the head of the waistcoat; an ultrasonic generator emits audio stimulation of specific brain wave guiding components, brain activities of a treated individual are guided to a deep relaxation or semi-sleep state mainly including alpha waves (8-12 Hz) and theta waves (4-8 Hz), and dominant defense and high-alertness reactions are reduced; by means of linguistic or audio meditation guidance, establishment of a safety scene is assisted, excessive activation of sympathetic nerves is reduced, and vagus nerve dominance is improved; the obvious improvement in the aspects of sleep, emotion, self value feeling and the like can be observed in 7-14 days; the original energy feeling is reprogrammed through a multi-layer path, the deep subconsciousness is changed, and the recurrence probability is low.

The present invention relates to the compositions comprising at least one cooling agent and at least one tingling agent for use in enhancing coldness perception in an individual. The present invention further relates to compositions and methods for improving mental alertness, cognitive performance, focus and / or sustained attention in an individual.

An ultrasound device for modulating brain activity may include a body and components for activating the brain. Such components include ultrasound transducers. The devices are used to provide ultrasound waves to brain structures in a subject wearing a device for methods to treat traumatic brain injury, affect postural control, affect wakefulness, attention, and alertness, to provide memory control, to alter cerebrovascular hemodynamics, to minimize stress, and to reinforce behavioral actions.

This application relates to a method and apparatus for acquiring alertness levels in the field of artificial intelligence, used to predict a user's alertness level by combining user behavior information collected by the device. The method includes: acquiring first information, the first information including information about user behavior, the first information including information collected by a first device, the first device including a wearable device of the user, and the first information including information about the user's ingested substances; and predicting changes in the user's alertness based on the first information, the changes in alertness including the user's alertness value within a first preset time period.

For each of a plurality of time intervals: a power spectrum is generated using a corresponding portion of EEG data; a normalized power spectrum is generated; and a preferred frequency (a frequency with a largest z-score or a highest normalized power in the normalized power spectrum corresponding to the time interval) or dominant frequency for the time interval is determined. A set of time windows is defined, each including multiple time intervals of the plurality of time intervals. For each of a set of time windows, a number of the time intervals is determined for which the preferred or dominant frequency is within a Beta band (12-30 Hz frequencies) or a portion thereof. For a time window, it is determined that an alert condition is satisfied using the number of the plurality of time intervals where the preferred or dominant frequency is within the Beta band or a portion thereof.

The invention discloses a micro-grid emergency control strategy generation method and system, and belongs to the technical field of micro-grid control, and the method comprises the steps: obtaining the operation information of a micro-grid, carrying out the arrangement, analyzing the data relevance based on the physical law of a power system, and carrying out the adaptive adjustment of an alertness range according to the operation state of the micro-grid. The method comprises the following steps of: selecting an alertness range of the microgrid, screening out deviations exceeding the alertness range, further analyzing deviation types, amplitudes, durations and related physical quantity combinations to identify an instability mode of the microgrid, and finally, evaluating a transient energy balance state of the microgrid according to the identified instability mode, determining a control quantity required for maintaining the stability of the system and issuing a control instruction. Due to fine identification of the instability mode, the control strategy can be more targeted, the problem of mismatching of the control quantity is avoided, oscillation can be effectively relieved, unnecessary load loss and economic cost are avoided, and the safe and reliable operation capacity of the micro-grid under the emergency situation is improved.

This application relates to the field of computer technology and discloses a method, device, and physiological modeling system for alertness calibration. The method includes: acquiring the reaction time of each subject in each task block for psychomotor alertness tasks; each task block consists of a psychomotor alertness task and an n-back task, or is composed solely of psychomotor alertness tasks; calculating the mean and standard deviation of each subject's task reaction time based on the reaction time of each task; calculating a personalized alertness grading threshold for each subject based on the mean and standard deviation; and generating an alertness level label for each subject corresponding to each task block based on the reaction time of each task using the personalized alertness grading threshold. This application can obtain objective, accurate, and realistic alertness label calibration results that conform to the actual changes in human alertness states.

A dialog device includes an alertness level calculation unit that calculates an alertness level of an occupant of a vehicle based on state information of the occupant, a dialog output unit that, in a case where the calculated alertness level is less than a predetermined value, outputs a dialog to the occupant, an interest degree calculation unit that calculates a degree of interest of the occupant in the dialog based on the state information after the dialog is output, and a dialog generation unit that determines a topic of the dialog based on the calculated degree of interest.

A method and system for determining morning alertness by leveraging the science of sleep inertia The method includes detecting sleep end time, monitoring heart rate and activity data post sleep end time. The method further includes calculating the active time based on the activity data of the user. Further, the method includes determining sleep inertia based on the sleep end time and the active time. The method further includes calculating a morning alertness score based on the sleep inertia. The morning alertness score is calculated by analysing the sleep inertia and activity data by a ML model. The morning alertness score offers insights into sleep effectiveness and psychological markers such as motivation.

A system for testing and training a brain capability of planning and executing motion activity for a user who has sustained a functional movement deficit; said system comprising an electroencephalographic sensor arrangement attachable to the head of said user; a processor configured for receiving and analyzing electroencephalographic signals obtained from said user during visualization of an action; a memory storing instructions when executed by said processor for instructing said user to visualize executing said motion action; measuring electroencephalographic signals on said electroencephalographic sensor arrangement; calculating at least one characteristic selected from the following: a concentration index; a motor control index; an alertness index; providing said user with a feedback pattern based on at least one said concentration, motor control, alertness and motion readiness; recurring steps to be if needed.

For each of a plurality of time intervals: a power spectrum is generated using a corresponding portion of EEG data; a normalized power spectrum is generated; and a preferred frequency (a frequency with a largest z-score or a highest normalized power in the normalized power spectrum corresponding to the time interval) or dominant frequency for the time interval is determined. A set of time windows is defined, each including multiple time intervals of the plurality of time intervals. For each of a set of time windows, a number of the time intervals is determined for which the preferred or dominant frequency is within a Beta band (12-30 Hz frequencies) or a portion thereof. For a time window, it is determined that an alert condition is satisfied using the number of the plurality of time intervals where the preferred or dominant frequency is within the Beta band or a portion thereof.

A system and method using a biomathetical model in conjunction with an optimization method for an individual's alertness impairment at a future time based on a known sleep schedule by adjusting the intake of caffeine over that schedule. In a further embodiment, placing constraints on the frequency, the dose amount, and / or total amount consumed over the course of the future schedule. In a further embodiment, optimizing the sleep schedule (prior to or independent of caffeine optimization) to decrease the individual's alertness impairment at the future time(s). In a further embodiment, adjust both the sleep schedule and caffeine intake to decrease the individual's alertness impairment at the future time(s). In at least one embodiment, the system including a mobile based system and / or a networked computer-based system.

This invention discloses an alertness detection method and system based on uncertainty measurement and cross-modal knowledge distillation, belonging to the fields of physiological signal processing and deep learning. Specifically, the method first preprocesses and extracts features from raw EEG and EOG signals to obtain structured EEG and EOG feature matrices, and generates alertness state labels based on the subject's behavioral reaction time index. Then, a teacher model is constructed and trained using EEG-EOG bimodal data as input; simultaneously, a student model is constructed using EOG unimodal data as input. Finally, using the trained teacher model as the knowledge source, the student model undergoes uncertainty-guided cross-modal knowledge distillation training. This method can effectively improve the alertness detection performance of the EOG unimodal student model under limited sample conditions.

A computer-implemented method for estimating awake-time alertness of a user includes: performing a recursive alertness prediction procedure by performing operations including: obtaining measurement data measured, from a user, by at least one sensor device; determining at least a sleep time, a sleep quality, and a circadian phase of the user; selecting, in response to a preceding awake-time alertness pattern enabled for usage in the recursive alertness prediction procedure, the preceding awake-time alertness pattern as an alertness pattern template; selecting, otherwise, a default alertness model as the alertness pattern template; determining an awake-time alertness pattern; and determining whether to enable or disable the awake-time alertness pattern determined for a subsequent recursive alertness prediction procedure; and causing displaying, to the user via a user interface, the awake-time alertness pattern determined.

Salts of hexylamine, for example, hexylamine succinate and tri-hexylamine citrate and their method of production are described. The disclosure also relates to compositions comprising hexylamine, for example, for reducing appetite in a human subject, treating obesity in a human subject, preventing obesity in a human subject, preventing weight gain in a human subject, increasing fat loss in a human subject, treating an overweight human subject, increasing athletic performance in a human subject, increasing endurance in a human subject, increasing muscle strength in a human subject, improving cognitive function in a human subject, treating ADHD in a human subject, increasing sweating in a human subject, reducing reaction time of a human subject, increasing psychomotor vigilance of a human subject, enhancing memory in a human subject, increasing central nervous system activity in a human subject, and enhancing alertness, attention, concentration, and / or memory in a human subject.

The invention relates to the technical field of medical equipment, and particularly discloses a helmet integrated type self-adaptive biological rhythm adjusting illumination device and method based on pupil tracking. The objective of the invention is to solve the problems that traditional illumination equipment cannot adapt to micro-motion of the head of a pilot, luminous flux loss and light beam diffusion caused by goggles, and circadian rhythm disorder caused by cross-time-zone flight. Infrared eye movement tracking, nine-axis IMU attitude data and environment sensing information are fused, a Kalman filtering and LSTM mixed model is adopted to predict pupil dynamic states, an MEMS reflector array and an electric control liquid crystal waveguide are combined to realize accurate focusing of light beams, real-time penetration compensation is carried out based on a goggle light transmittance database, and the real-time penetration compensation is realized. And dynamically adjusting the illumination parameters of the blue / green / red three wavebands according to the flight stage and the physiological characteristics of the pilot. High-precision, low-delay, personalized and environment-robust self-adaptive illumination regulation and control of the biological rhythm of the pilot can be realized, and the alertness and rhythm stability in a day and night flight task are remarkably improved.

The application provides a brain fatigue dynamic early warning method and device, computer equipment and a storage medium, and belongs to the field of traffic safety. The method comprises the following steps: obtaining a pupil diameter entropy time sequence, a gaze entropy time sequence, time characteristics and a preset task stage label of a driver; preprocessing the above characteristics respectively, splicing the preprocessing results, and obtaining a joint feature matrix; performing time sequence feature extraction on the joint feature matrix, and generating shared hidden features; generating distribution parameters of cognitive load, fatigue state and alertness state from the shared hidden features respectively, and then determining state values of the fatigue state and the alertness state from the distribution parameters through reparameterization sampling; and performing early warning according to the state values of the fatigue state and the alertness state in combination with a driving scene. In this way, the application realizes determination of the brain fatigue state through the pupil state by means of multi-modal fusion, mechanism constraint decoupling and dynamic risk assessment, and can reduce the traffic accident rate caused by fatigue in the field of driving safety.