41 results about "Wakefulness" patented technology

A device and / or method for detecting a second instance of sleep onset within a nighttime treatment period according to a second criterion different from a first criterion associated with a first instance of sleep onset during the nighttime treatment period.

To estimate an arousal direction of a driver of a vehicle.SOLUTION: A first derivation unit 41 derives a first index value corresponding to a driver's visual stimulation based on a front image of a vehicle obtained by an imaging unit. A second derivation unit 42 derives a second index value corresponding to a relatively strong visual stimulation among a driver's visual stimuli based on a result of comparing the first index value with a predetermined stimulation threshold. An arousal direction estimation unit 43 estimates an arousal direction, which is a direction of change in the driver's arousal level, based on a correlation between a temporal change in the first index value and a temporal change in the second index value.SELECTED DRAWING: Figure 9

The invention provides a dialogue device, a dialogue method, and a computer program product, which can realize a dialogue with a good waking effect to an occupant. A dialogue device is provided with: a degree-of-consciousness calculation unit that calculates the degree of consciousness of an occupant of a vehicle on the basis of state information about the occupant; a dialogue output unit that outputs a dialogue to the occupant when the calculated degree of wakefulness is less than a predetermined value; an interestingness calculation unit that calculates the interestingness of the occupant in the conversation on the basis of the state information after the conversation is output; and a dialogue generation unit that determines a topic of the dialogue on the basis of the calculated interestingness.

According to an aspect, there is provided an apparatus (100) for assessing sleep of a subject, the apparatus comprising a processor (102) configured to: receive data indicative of one or more physiological parameters associated with a subject; determine, based on the data, two or more sleep parameters relating to sleep of the subject; and determine, based on the sleep parameters, whether the subject is suffering from (a) obstructive sleep apnoea, (b) insomnia, (c) comorbid insomnia and obstructive sleep apnoea, or (d) neither obstructive sleep apnoea nor insomnia, wherein a first sleep parameter of the two or more sleep parameters comprises Wakefulness After Sleep Onset for at least X Minutes, WASOXmin, wherein WASOXmin comprises the sum of awakenings with a duration of X minutes or longer during a sleep session, wherein X is equal to, or greater than, 1.

The invention relates to a self-adaptive control method and device for a vehicle-mounted entertainment information system, and belongs to the technical field of vehicle control, and the self-adaptive control method for the vehicle-mounted entertainment information system comprises the steps: obtaining the video stream data of an area where a target child is located, determining the metadata of a target picture book based on the video stream data, the metadata comprises a picture book theme, a picture book name and a picture book tone, the efficiency value is used for representing the positive degree or negative degree of emotion, the wake-up degree is used for representing the intense degree of emotion, and the concentration degree is used for representing the cognitive input degree; based on the metadata of the target picture book, determining a first control instruction used for controlling a vehicle-mounted audio system and a second control instruction used for controlling a vehicle-mounted atmosphere lamp system; and adjusting the first control instruction and the second control instruction based on the efficiency value, the wake-up degree and the concentration degree of the target child. According to the invention, the riding experience and riding safety of children are effectively improved.

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 discloses an intelligent cockpit driver and passenger real-time detection device and an operation method.The intelligent cockpit driver and passenger real-time detection device comprises an intelligent seat, a human brain monitoring and protecting device, a reinforced awakening mechanism and a steering wheel anti-disengaging mechanism, and the intelligent seat comprises a headrest, a backrest and a cushion; the human brain monitoring and protecting device is movably connected to the end face of one side of the headrest and comprises a pair of head air bag protecting assemblies and a pair of electroencephalogram evaluators, and the head air bag protecting assemblies are fixedly connected to the end faces of the inner sides of the electroencephalogram evaluators; the head air bag protection assembly and the electroencephalogram evaluator are matched with the head of a person after being combined. The driver needs to put the head back into the human brain monitoring and protecting device regularly to monitor the current physical condition and waking condition, data is transmitted back to a background monitoring system in real time, and once abnormity is found, early warning is given out in time, the driver is informed to stop driving, and processing is carried out in time.

Techniques for configuring one or more applications based on a detected wakefulness state of a user are disclosed. A system trains and applies a machine learning model to wakefulness data to compute a wakefulness state of a user. The system obtains the wakefulness data from wearable devices worn by the user and environmental devices in a user's environment. The system configures applications and / or devices based on the computed wakefulness state of the user. The system configures the ability of devices or applications to generate visual, audible, or tactile notifications in response to determining that a user is awake or asleep.

A dual-phase sleep aid supplement designed to promote restful sleep and enhance wakefulness. The supplement includes an immediate release layer containing sleep-promoting ingredients and a delayed release layer of caffeine designed to release after 6-8 hours. The formulations include options with melatonin or vitamin B12 and tryptophan.

The invention discloses a pillow recommendation method and device and a training method of a cervical vertebra supporting state prediction model.The method comprises the steps that waking state data of a user lying on a test pillow in a waking state are collected, and the waking state data comprise a head, neck and shoulder pressure distribution diagram of the user in the waking state; the waking state data are input into a pre-trained cervical vertebra supporting state prediction model to obtain sleep state data of the user in a deep sleep state, and the sleep state data comprise a head, neck and shoulder pressure distribution diagram of the user in the deep sleep state; and recommending a pillow to the user according to the sleeping state data. Therefore, the cervical vertebra supporting state of the user after the user enters deep sleep by using the pillow can be accurately predicted.

To provide a technology that suppresses a decrease in efficiency of controlling a user's wakefulness state.SOLUTION: A wakefulness state control system includes a sensor that acquires biometric information of a user, and a stimulus imparting device that imparts stimuli to the user to control the wakefulness state based on vital values obtained from the biometric information that serve as indicators of the user's wakefulness state. The stimuli imparted by the stimulus imparting device include a relaxing stimulus that leads the user's vital value change rate in a negative direction, an awakening stimulus that leads the vital value change rate in a positive direction, and a super-awakening stimulus that is greater than the awakening stimulus and leads the vital value change rate in a positive direction. The vital value change rate is a rate of change in the vital value when the stimulus is applied, relative to a predetermined standard vital value.SELECTED DRAWING: Figure 1

This invention discloses an endocrine rhythm-driven PPO full-spectrum intelligent dimming system, comprising a multi-dimensional data perception layer, an edge computing and core decision-making layer, and a light control execution layer. The multi-dimensional data perception layer includes a front-end high-resolution spectral sensing sensor module and a wearable device interface module; the edge computing and core decision-making layer includes a standardized feature dataset architecture unit, an endocrine multi-axis coupling prediction unit, and an AI decision model; the light control execution layer includes a five-channel visible light driving controller and a full-spectrum LED light-emitting module. This invention can offset rhythm deviations caused by environmental interference light sources in practical application scenarios, ensuring that the composite light entering the eye always conforms to the preset physiological regulation target, achieving the purpose of precise dimming, and can provide deep-level photoneurophysiological gains, synergistically improving the user's sleep quality and wakefulness.

The present disclosure relates to a method and system for acquiring and analyzing physiological signals of a subject to detect the risk or occurrence of stroke or cerebral infarction. A wearable wireless device may be used with one or more electrode clusters to record physiological signals during a sleep-wake cycle. The physiological signal may be utilized to perform sleep and wakefulness analysis. In some examples, physiological signals corresponding to each hemisphere of the brain may be compared, e.g., using coherence, to quantify asymmetry across the hemispheres and identify possible stroke, asymptomatic cerebral infarction (SBI), or aneurysm. Biomarkers may be extracted based on sleep and wakefulness analysis as well as coherence. Biomarkers may include an indication of obstructive sleep apnea or apnea risk, a reduction in slow wave sleep duration, or the presence of SBI or aneurysm. A stroke risk score may be generated from the biomarkers using a predictive model for the early detection of individuals that are potentially at risk of stroke.

The present application relates to the field of intelligent health monitoring and digital technology of traditional Chinese medicine, and particularly relates to a traditional Chinese medicine sleep health monitoring system based on millimeter wave radar. The system comprises: a data acquisition module for acquiring original vital sign signals through millimeter wave radar; a data processing module for extracting a sleep physiological parameter set; a sleep staging identification module for identifying sleep staging results corresponding to wakefulness, light sleep, deep sleep and rapid eye movement; a traditional Chinese medicine sleep evaluation module for converting sleep parameters into traditional Chinese medicine quantitative indicators through a quantitative mapping unit, generating traditional Chinese medicine syndrome differentiation labels through a space-time correlation unit, and outputting traditional Chinese medicine health monitoring results after fusion analysis by an analysis and decision unit; and a monitoring result output module for generating a visual health report. The present application realizes the deep integration of non-invasive, continuous sleep monitoring and objective, quantitative traditional Chinese medicine syndrome differentiation, and provides a systematic solution for sleep health management.

The invention relates to the technical field of intelligent wearable equipment, in particular to a multi-stage alarm clock wake-up system based on biological signal recognition, which collects and fuses multi-modal physiological signals in real time through wearable equipment, dynamically calculates wake-up demand indexes and accurately recognizes sleep stages. Graded combined stimulation of vibration, acoustics and electric tactile sense is adaptively triggered based on the sleep depth, and a mobile terminal remote cooperative control and multi-device networking enhancement mechanism is combined; meanwhile, a gesture detection closed loop is used for verifying the waking state, the stimulation intensity is automatically upgraded when no response is made, and finally progressive waking-up matched with the sleep cycle is achieved. Therefore, the wake-up success rate in the deep sleep period is remarkably improved, the phenomenon of secondary falling asleep is eliminated, and the user experience is improved through collaborative decision while ultra-low power consumption is maintained.

The application relates to the technical field of anesthesia post-complication monitoring, in particular to an intelligent early warning system for post-anesthesia complications of surgical patients. The system obtains the intraoperative risk degree according to the size and change of the intraoperative body index data of the patient in each first preset time period, the past medical history score and the allergy history score of the patient, and then judges the intraoperative anesthesia complication patients and the intraoperative normal patients in real time; the postoperative risk degree is obtained according to the size of the postoperative body index data of the intraoperative normal patient in each second preset time period, the consciousness state score, the nervous system score, the wound recovery score and the wakefulness state of the intraoperative normal patient, and the intraoperative risk degree of the intraoperative normal patient, and then the postoperative anesthesia complication patients and the postoperative normal patients are judged in real time. The intraoperative risk degree and the postoperative risk degree are accurately obtained in real time, so that the post-anesthesia complications of the patient can be accurately detected in time, and measures can be taken in time, and the harm of the post-anesthesia complications is effectively reduced.

The application discloses a sleep optimization system based on brain wave regulation, and relates to the technical fields of sleep health and electroencephalogram regulation, comprising a hierarchical gap dynamic mapping module, a gap resonance compensation module, a cross-layer interlocking calibration module and a gap feature adaptive memory module, and the four modules form a closed loop collaborative work; in the application, the closed loop collaborative technology of the hierarchical structure of brain waves, three-dimensional gap feature dynamic mapping, targeted resonance compensation suitable for sleep stages, cross-layer interlocking calibration and two-dimensional clustering self-optimization of stage gaps is used, the problems that the existing sleep optimization system does not use the brain wave hierarchical division mechanism, the single frequency band regulation has poor adaptability, the multi-frequency band regulation is easy to produce signal interference and has low efficiency, and the deep sleep is not continuous and the wakefulness is residual are solved, the precise adaptation to sleep stages and individual differences is realized, the frequency band interference is eliminated, the continuity and proportion of deep sleep are improved, and the residual wakefulness and shallow sleep wandering are reduced, so that the safe and efficient personalized sleep optimization effect is achieved.

Techniques are disclosed for facilitating disabling an alarm in response to particular types of activity-indicative data. More specifically, activity-indicative data (e.g., measurements obtained by an electronic device) can be detected prior to a preset alarm time. Upon determining, based on the activity-indicative data, that a wakefulness condition is satisfied, the alarm can be disabled such that the alarm stimuli is not to be presented at the preset alarm time.

The present disclosure generally relates to systems and methods for monitoring and / or the sleep stage of an individual using one or more sensors, and methods of treating medical conditions related thereto (e.g., obstructive sleep apnea).

The application discloses a kind of methods for detecting fatigue state variable using driver eye image, comprising the following steps: S01, construct a kind of priori Gaussian model, for expressing eye structure;S02, the priori Gaussian model in S01, for each eyeball or eye white, set its two-dimensional distribution such as expression;S03, design Gauss EyeNet network;S04, after obtaining segmentation map in S03 step, fatigue state variable is solved.The application proposes a kind of full convolution segmentation network Gauss EyeNet fusing Gaussian distribution according to the characteristics of eye tissue structure distribution, constructs fatigue state variable feature by pixel-level analysis eyeball and eye white relationship, and reduces the influence brought by individual difference by normalization strategy.Gaussian strong priori hypothesis enhances the stability of detection, compared with the means of traditional classifier, the method of the application can accurately express a variety of fatigue state variables, and the extracted index can better distinguish between wakefulness and fatigue.

The invention discloses an electroencephalogram awakening degree classification method and system based on multi-period dynamic rhythm characteristics, and relates to the technical field of biomedical engineering. The method comprises the following steps: acquiring an electroencephalogram signal of a testee; segmenting the electroencephalogram signal of each channel by using a plurality of preset time windows to correspondingly obtain electroencephalogram signals of a plurality of time periods; respectively carrying out time-frequency analysis on the electroencephalogram signals of each channel in each time period to obtain a time-frequency spectrum, and extracting dynamic rhythm characteristics based on the time-frequency spectrum; and inputting the dynamic rhythm characteristics into a double-layer heterogeneous decision model, and predicting the electroencephalogram wake-up degree category. According to the method, the dynamic rhythm characteristics of the time-frequency spectrum in each short time period are extracted, and the wake-up state of a single subject is classified by utilizing the dynamic rhythm characteristics and the double-layer heterogeneous decision model and using a small amount of data identification, so that the dynamic response process of the electroencephalogram signal to short-time stimulation can be well captured; and the accuracy of electroencephalogram awakening degree classification is improved.

The invention relates to the technical field of sleep assistance, and discloses a sleep adjuvant therapy device based on white noise, the sleep adjuvant therapy device comprises a buffer cushion mechanism and a soft light wake-up mechanism, the surface of the buffer cushion mechanism is wrapped with a protection variable temperature wake-up mechanism, and the input end and the output end of the protection variable temperature wake-up mechanism are provided with water pumping mechanisms. According to the sleep adjuvant therapy device based on the white noise, by arranging the buffering supporting cushion mechanism, the protection variable-temperature awakening mechanism, the water pumping mechanism and the soft light awakening mechanism, soft white light can be projected through the soft light awakening mechanism in the awakening stage, and the protection variable-temperature awakening mechanism and the water pumping mechanism are linked to generate gradually-cooled mild somatosensory stimulation; meanwhile, the buffer supporting cushion mechanism generates white noise which is gradually increased from weak to strong, and the three parts are superposed in sequence to simulate a natural awakening environment, so that the user is stably and progressively transited to be awakened from a deep sleep state, and physiological discomfort and sleep inertia in the awakening process are effectively reduced.

Provided are a driving assistance device, a driving assistance method, and a recording medium whereby it is possible to select a more appropriate countermeasure against a decrease in the wakefulness of a driver.　The driving assistance device comprises: an acquisition means that acquires a facial image of a driver of a vehicle; a measurement means that measures the wakefulness of the driver on the basis of at least the degree of openness of the eyes in the facial image of the driver; a situation comprehension means that comprehends the travel environment of a road on which the vehicle is traveling; and a selection means that selects a countermeasure for the driver on the basis of the travel environment and the wakefulness level of the driver.

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.

The present application provides a composition, food and application thereof for improving sleep. The composition comprises phosphatidylcholine, and further comprises one or more of the following: spina date seed and / or extract thereof, poria cocos and / or extract thereof. The present application develops a composition for improving sleep, which can improve the state of easy wakefulness after sleep; improve the state of not easy to fall asleep; improve the quality of sleep depth; improve the sleep phase delay disorder; and / or improve the state of anxiety and / or the state of neurasthenia caused by the decrease of sleep quality.

The invention discloses a composition of GABA (gamma-aminobutyric acid), tremella polysaccharide and theanine as well as a preparation method and application of the composition. The composition comprises a mixture of the tremella polysaccharide and the theanine and the GABA. The mass ratio of tremella polysaccharide to theanine in the mixture is 10: 1; the mass ratio of the mixture of the tremella polysaccharide and the theanine to the GABA is 150: 100. The invention proves that when the GABA and the mixture are compounded according to a specific proportion for use, the GABA and the mixture show a remarkable synergistic effect in the aspects of promoting falling asleep, maintaining sleep, increasing non-rapid eye movement sleep and resisting caffeine-induced awakening, and a solid experimental basis is provided for developing an efficient composite sleep-aiding product.

The application discloses a method for determining sensitive brain areas and electroencephalogram features for fatigue detection. The method comprises the following steps: selecting multiple signal collection positions on the head and collecting wakefulness electroencephalogram signals and fatigue electroencephalogram signals; determining multiple wakefulness electroencephalogram features and multiple fatigue electroencephalogram features according to the wakefulness electroencephalogram signals and the fatigue electroencephalogram signals collected at each signal collection position; determining the difference degree of the same type of wakefulness electroencephalogram features and fatigue electroencephalogram features at each signal collection position and sorting to obtain a sorting result; and selecting sensitive brain areas and electroencephalogram features for fatigue judgment from the signal collection positions and electroencephalogram features within a preset high difference degree range according to the sorting result. The above method can select sensitive brain areas and electroencephalogram features that are more conducive to fatigue detection. The application also discloses a device for determining sensitive brain areas and electroencephalogram features for fatigue detection, a fatigue detection method, an electronic device and a computer readable storage medium.

The present disclosure relates to a system and method for managing a subject's sleep state during a medical examination. In particular, the present disclosure may provide systems and methods for monitoring a subject's sleep state and adjusting the operation parameters of a subject engagement system based on the subject's current sleep state and a target sleep state. Disclosed embodiments thus enable the automatic adjustment of the subject's environment to either facilitate sleep or wakefulness. This may be particularly beneficial during lengthy medical procedures, such as MRI scans, where subjects often fall asleep.

The invention is applicable to the technical field of medicine, and provides application of spinosin in preparation of medicine for promoting non-rapid eye movement sleep, spinosin shortens the sleep latency period of mice, increases NREM sleep duration and reduces wakefulness; different from benzodiazepine drugs, spinosin does not change the EEG power spectrum density and does not affect the exercise performance in a rotating bar test, which indicates that spinosin is suitable for treating insomnia. The invention solves the problems of adverse reaction and reduction of sleep quality of the existing hypnotics, and is suitable for treating insomnia, especially insomnia accompanied with anxiety and neurological disorders.

The application discloses a kind of piano performance brain fatigue regulation effect quantification evaluation method, including constructing test scene, respectively collecting the pulse wave signal and performance behavior data of subject wakefulness, fatigue, performance end;Extract physiological characteristics in pulse wave signal, and important evaluation and screening are carried out, and weight is determined according to importance;Extract performance behavior characteristics;Statistical relationship analysis is carried out to the change amount of performance behavior characteristics and physiological characteristics, constructs the regulation model of performance behavior characteristics to physiological characteristics weight, calculates weight regulation factor;The change amount of physiological characteristics is weighted fusion, and the output comprehensive fatigue regulation index is output.The application carries out multidimensional brain fatigue regulation effect evaluation by fusing physiological signal and performance behavior, overcomes the limitation that traditional evaluation relies on subjective report or single physiological index, realizes objective, continuous, quantifiable evaluation to piano performance intervention effect, reduces subjective evaluation deviation, improves scientificity and reliability.