70 results about "Sleep behavior" patented technology

The invention discloses a sleep report generation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring basic information, historical sleep data and behavior data of a target object; dividing a group type of the target object based on the basic information, and determining a first attention score of the target object on the target sleep index according to group type mapping; counting sleep behaviors based on historical sleep data to construct a sleep problem label of the target object, and mapping and determining a second attention score of the target object to the target sleep index according to the sleep problem label; the attention of the target object to the target sleep index is obtained based on behavior data statistics, and a third attention score of the target object to the target sleep index is determined according to attention mapping; and performing weighted summation on all attention scores corresponding to the target sleep index, and outputting a sleep report of the target object according to a weighted summation result. The sleep report can be generated in a personalized mode, and the method can be widely applied to the technical field of data processing.

The invention discloses a multi-sleep behavior activity identification method and system in the technical field of acoustic sensing, and aims to solve the optimization problem of the existing multi-sleep behavior activity identification technology. The method comprises the following steps: preprocessing a collected dual-track acoustic signal in an ear canal of a user to obtain a processed dual-track acoustic signal; according to the processed dual-track acoustic signal, sleep behavior event detection and segmentation are carried out based on an adaptive detection and segmentation algorithm of a dynamic threshold, and a sleep event set is obtained; according to the sleep event set, sleep behavior events are classified based on accumulated spectrum power, and a sleep body activity event set and a sleep acoustic activity event set are obtained; according to the sleep body activity event set, based on acoustic attenuation and accumulated spectrum power, performing fine-grained identification of body activity events; and performing multi-dimensional feature extraction according to the sleep acoustic activity event set, and performing fine-grained identification of the acoustic activity events by using the extracted multi-dimensional features.

The invention provides a system for early predicting the incidence of obstructive sleep apnea diseases based on sleep behaviors. Specifically, the invention provides a sleep behavior-based early obstructive sleep apnea (OSA) disease occurrence risk assessment system, which comprises (a) an input module configured to input sleep behavior data of a certain object; (b) an evaluation module which is configured to perform preliminary evaluation on the input sleep behavior data, obtain a sleep score and perform discrimination processing; and (d) an output module configured to output the evaluation result value. The system provided by the invention can predict chronic obstructive sleep apnea more effectively, more early and more accurately, and provides effective prevention suggestions.

The invention provides a sleep behavior detection method and device and electronic equipment, and the method comprises the steps: carrying out the detection of a current video image for each frame of video image in a to-be-detected video, and obtaining a detection result; if it is determined that at least one first detection frame exists according to the detection result, obtaining a camera identifier corresponding to the current video image; if it is determined that historical time information and at least one historical detection frame of a previous frame of video image corresponding to the camera identifier exist according to the camera identifier, detecting whether a sleep behavior exists through a DHash algorithm based on current time information and historical time information of a current video image, each first detection frame and each historical detection frame; according to the mode, the current time information of the current video image, each first detection frame, and the historical time information and each historical detection frame of the previous frame of video image can be combined, and the DHash algorithm is used to detect whether the sleep behavior exists, so that the detection accuracy of the sleep behavior can be improved.

A device for monitoring a sleep state of a community mounted on each measurement target forming the community includes an electrode unit configured to measure biosignals including an electroencephalogram (EEG) and electromyography (EMG) of each measurement target forming the community, a control unit configured to compare the measured EEG andEMG with critical values and classify sleep and wake states of the measurement target, an indicating unit configured to emit light in different colors according to the sleep and wake states of the measurement target, and a recording and communication unit configured to store or transmit the measured EEG and EMG to an external device. Therefore, by measuring a sleeping behavior of each entity of the community and analyzing and visualizing the sleep and wake states in real time, it is possible to efficiently observe the interaction between sleep and an environment.

The present invention relates to the field of medicine and of dietary supplements, in particular the technical (i.e. medical-pharmaceutical or food-technology) field of sleep problems and sleep disorders. In particular, the present invention relates to a dosage form, in particular a dietary-supplement dosage form or pharmaceutical dosage form, in particular for oral administration, preferably for promoting or supporting sleep health or sleep behavior or preferably for use in the prophylactic or therapeutic treatment of sleep disorders or dysregulation of the natural day / night rhythm or the circadian rhythm.

The invention discloses a sleep behavior monitoring method and device, a storage medium and a terminal, and the method comprises the steps: obtaining a cover image corresponding to a sleep event video, the sleep event video being a video collected for a sleep event in a current scene through a sleep monitoring device; the cover image is input into a large action recognition model, sleep actions output by the large action recognition model based on the cover image are determined, and the sleep actions are normal sleep actions or quilt kicking actions; and when the sleep action is a quilt kicking action, generating first notification information corresponding to the quilt kicking event, and sending the first notification information to a target terminal bound with the sleep monitoring equipment, so that the target terminal displays the first notification information. And the server can analyze the cover image by using the action recognition large model, so that the sleep action of the user is obtained. In this way, when the user kicks the quilt, the corresponding prompt notification information can be sent to the bound target terminal in time, and the sleep experience of family members is improved.

The invention relates to a respiratory nephropathy department patient sleep nursing system and method based on intelligent monitoring, equipment and a medium. Comprising a physical sign acquisition module, a data processing module, an environment monitoring module, an illness state prediction module and a nursing intervention module. The physical sign acquisition module is responsible for monitoring physiological parameters and sleep behaviors of a patient during sleep in real time, and the data processing module performs analysis and evaluation according to physiological feature data and sleep behavior data to obtain a sleep quality evaluation result of the patient. The environment monitoring module monitors environment parameters of a sleep environment of a patient in real time to obtain environment characteristic data. And the illness state prediction module predicts the illness state change of the patient by using a trained prediction model based on the environment feature data, the physiological feature data and the sleep behavior data to obtain a predicted illness state trend. And the nursing intervention module performs analysis according to the sleep evaluation result and the predicted illness state trend to obtain an environment regulation scheme suitable for sleep of the patient. And comprehensive monitoring and optimization of sleep and illness conditions of the patient are realized.

The invention discloses a multi-source snore recognition and analysis system based on a single microphone. The system comprises an audio acquisition module for acquiring audio signals in an environment, a signal preprocessing module connected with the audio acquisition module and used for processing the acquired audio signals, and a multi-scale convolutional neural network feature extraction module connected with the signal preprocessing module and used for extracting time-frequency features of the signals through a multi-scale CNN. The GRU time sequence processing module is connected with the multi-scale convolutional neural network feature extraction module, carries out time sequence information optimization on the extracted time-frequency features and generates separated snore features, and the sleep behavior analysis module is connected with the GRU time sequence processing module, detects snore feature signals and generates a visual sleep report. The method has the advantages of being low in hardware cost, simple, wide in application scene and beneficial to popularization based on the single microphone.

The invention belongs to the technical field of traditional Chinese medicine compound preparations, and particularly relates to a qi-regulating, phlegm-reducing and nerve-calming paste, a preparation method thereof and application of the paste in preparation of a medicine for treating Parkinson's disease combined with rapid eye movement sleep behavior disorder. The paste is prepared from the following raw materials in parts by weight: 9-30 parts of semen ziziphi spinosae, 15-30 parts of Chinese yam, 10-15 parts of poria with hostwood, 9-30 parts of semen coicis, 3-10 parts of pericarpium citri reticulatae, 3-10 parts of fingered citron, 10-20 parts of sesame, 10-20 parts of rock candy and 3-5 parts of maltose. By nourishing the heart and strengthening the spleen to consolidate the root, regulating qi and reducing phlegm to relieve stagnation and tranquilizing and sedating the physique to return to the soul, the three methods are combined to achieve the purposes of tonifying without stagnation, eliminating without injury, recovering the heart and the spleen, smoothing phlegm and qi and self-hiding the soul.

The invention belongs to the technical field of biological medicines, and particularly relates to application of an mTOR inhibitor to improvement of sleep disorders. Aiming at the defects of the existing hypnotics, the invention finds that the sleep disorder can be improved by using the Rapamycin through researching a new sleep pathway target. The Rapamycin disclosed by the invention is a non-addictive sleeping drug, and can induce natural sleep behaviors; compared with an existing clinical hypnotics which has the side effect of greatly increasing the death rate, the Rapamycin administration disclosed by the invention is beneficial to improving the sleep quality and prolonging the life of animals at the same time. The invention discloses a remarkable effect of Rapamycin in the aspect of improving the sleep disorder, and the discovery has important significance in improving the sleep quality of a patient and preventing the progress of diseases, so that the Rapamycin has a wide medical prospect and a remarkable economic value.

The invention discloses an unattended sleep quality analysis method and system, and the method comprises the steps: obtaining sleep related signals from the surrounding environment of a user through a non-contact sensor technology, carrying out the real-time capturing of body movement frequency characteristics and breathing rhythm characteristics, and obtaining a preliminary sleep behavior data record; according to the initial sleep behavior data record, filtering the body movement frequency signal and the breathing rhythm signal by adopting a signal denoising processing method, eliminating environmental noise interference, and determining an optimized sleep signal data set; aiming at the optimized sleep signal data set, performing feature extraction by utilizing a pre-established sleep stage classification model, analyzing regular changes of a body movement mode and a breathing law, and judging a sleep stage distribution condition of the user; according to the sleep stage distribution condition, the sleep quality of the user is graded and evaluated in combination with the preset threshold range, and accurate sleep stage judgment and sleep quality evaluation can be achieved.

The invention belongs to the technical field of medical health monitoring and behavior intervention, and discloses a pre-school autism sleep personalized intervention system based on AI behavior analysis, which comprises a behavior acquisition unit, an environment monitoring unit, a living habit management unit, a fusion analysis unit, an intervention execution unit, a self-adaptive optimization unit and a family interaction unit, according to the system, body movement, heart rate, skin electricity and sleeping posture information of children and environment parameters such as illumination, noise and temperature and humidity of a bedroom are synchronously collected, diet and exercise balance indexes are combined for fusion analysis, and behavior risk indexes are generated; a personalized intervention scheme is automatically generated according to the risk level, and intervention is implemented through light, sound and visual guidance modes. The system dynamically adjusts analysis parameters according to an intervention result, realizes closed-loop correlation analysis and continuous regulation and control of sleep behaviors, environment changes and parent feedback, and is suitable for individualized sleep management of children with autism.

The invention discloses a sleep scene-oriented bimodal fusion radar dynamic attitude identification method and device. The method comprises the following steps of: S1, acquiring and demodulating radar original data; s2, double-window feature construction of a velocity mode and a structural mode; s3, carrying out speed-guided dual-mode time alignment and feature reweighting; s4, the dynamic sleeping postures are output in a classified mode. According to the method, the limitation of an existing single-mode radar processing method in the aspects of weak action visibility, bedding shielding robustness and directivity discrimination capability is broken through, and a new implementation mode is provided for whole-process dynamic posture monitoring of complex sleep behaviors.