101 results about "SLEEP APNEA (device)" patented technology

The invention discloses a sleep apnea type distinguishing method and device based on a millimeter wave radar, and a computer readable storage medium. The method comprises the following steps: acquiring a millimeter wave radar echo signal of a monitored object in a monitoring area; extracting body movement signal characteristics, thoracic cavity reflection signal energy characteristics and respiratory signal amplitude characteristics from the echo signals; on the basis of the extracted body movement signal features, the chest reflection signal energy features and the respiratory signal amplitude features, constructing a feature sequence with a time sequence; and inputting the feature sequence into a pre-trained classification model based on a self-attention mechanism to perform dynamic correlation analysis, and determining the sleep apnea type of the monitored object. The method has the advantages of non-contact type, accurate distinguishing of sleep apnea types and the like.

The application belongs to the technical field of medical signal processing, and discloses a sleep apnea detection method and system, an electronic device and a storage medium. The method comprises the following steps: acquiring a synchronous ECG signal and a breathing signal, and processing the synchronous ECG signal and the breathing signal into a bimodal data segment containing multiple time scales; constructing a parallel neural network architecture, extracting ECG features and breathing signal features from each scale data segment respectively, and forming a cross-modal feature pair; designing a cross-scale dynamic weight correction attention mechanism, introducing a correction factor based on the Euclidean distance between feature vectors, dynamically weighting and information fusion on the cross-modal feature pair between different scales, so as to enhance the relevance of local details and global context; inputting the fused multi-scale features into a classifier, and outputting the probability of a sleep apnea event. Through multi-scale collaborative analysis and a dynamic weight correction attention mechanism, the application effectively fuses physiological information of different time dimensions, and improves the detection accuracy.

The invention discloses a sleep apnea detection method and device and electronic equipment. The method comprises the following steps: acquiring target physiological signal data corresponding to a target object; extracting target respiratory signal data from the target physiological signal data; calling a reference frequency amplitude fluctuation index; according to the target respiratory signal data, multiple pieces of sub respiratory signal data are determined; determining sub-respiration frequency amplitude characteristics corresponding to the multiple pieces of sub-respiration signal data; and determining an apnea detection result of the target object according to the reference frequency amplitude fluctuation index and the sub-respiration frequency amplitude characteristics corresponding to the multiple pieces of sub-respiration signal data. The sleep apnea detection method and the sleep apnea detection device solve the technical problem that sleep apnea detection is inaccurate when sleep apnea detection is carried out according to physiological signals.

A hose retaining device is disclosed herein. The hose retaining device includes a strap assembly coupled to a padding portion having a top surface, a protruding member, and a retaining loop. The strap assembly further includes hook portion, a loop portion, and a fastening slot for turning the strap assembly back upon itself to couple the hook portion to the loop portion. The retaining loop includes an underside configured to receive and retain a corrugated tubing having a plurality of sunken portions and a plurality of protruding portions. The hose retaining device is useful for keeping a corrugated tubing item, commonly used in conjunction with a breathing assistance device, out of the way of the user to increase comfort and stability.

The invention discloses a sleep apnea monitoring system based on non-contact intervention, and belongs to the technical field of medical health monitoring. The method solves the problems that in the prior art, a PSG method is tedious in operation and high in cost, household contact equipment brings discomfort to a user, and natural sleep is affected, physiological signals are collected through a non-contact biological radar sensor, an initial threshold value, an auxiliary threshold value and an environment factor are synthesized to calculate an optimal threshold value, and the optimal threshold value is obtained. The detection accuracy of the apnea and hypopnea events is improved; in combination with the apnea hypopnea index, the event duration factor, the blood oxygen decreasing factor and the event type factor, severity scores are calculated, and the patients are divided into mild patients, moderate patients and severe patients; according to the severity, the grade and the snore type of the real-time event, the optimal intervention measure is selected from the intervention strategy library, personalized intervention is achieved, interference to sleep of the patient is reduced, and the sleep quality and the life quality are improved.

Sleep apnea prediction using electrocardiograms and machine learning is described. In one or more implementations, a wearable monitoring device produces electrical potential measurements of a heart of a user during an observation period spanning multiple days. A sleep apnea classification of the user is predicted by providing the electrical potential measurements to one or more machine learning models as input. The one or more machine learning models are trained based on historical electrical potential measurements and historical outcome data of a user population to correlate patterns in electrical potential measurements to sleep apnea classifications. The sleep apnea classification may then be output, such as in a health report, via a user interface, as notification on a computing device, and so forth.

Exemplary systems, methods, and devices are disclosed which provide at-home, portable, wireless sleep sensors and wearable electronics with embedded machine learning. Such devices have applications in assessing sleep quality and detecting sleep apnea with multiple patients. Unlike the conventional system at a sleep center using numerous bulky sensors, the soft all-integrated wearable platform offers natural sleep in a familiar setting. The face-mounted patches that detect brain, eye, and muscle signals show comparable performance in sleep monitoring with polysomnography in a clinical study. Furthermore, deep learning is embedded in an exemplary device, offering automated high-precision sleep scoring, which demonstrates the wearable system's portability and point-of-care usability. The at-home wearable patches help to support portable sleep monitoring and home healthcare.

The invention relates to a sleep apnea detection method and device, embedded equipment and a storage medium. The method comprises the steps of obtaining PPG signal data of a user during sleep, preprocessing the PPG signal data to obtain a plurality of PPG signal segments, extracting a one-dimensional time sequence feature vector used for reflecting the change condition of heart rate and blood flow for each PPG signal segment, converting the PPG signal segments into two-dimensional frequency spectrum images, and outputting the two-dimensional frequency spectrum images. Extracting a two-dimensional image feature vector used for reflecting spectrum structure characteristics based on the two-dimensional spectrum image, fusing the one-dimensional time sequence feature vector and the two-dimensional image feature vector to obtain a fused feature vector, and performing standardization and dimension reduction processing on the fused feature vector to obtain a target feature vector; and inputting the target feature vector into a trained classification model for classification to obtain a classification result of whether the PPG signal segment has the apnea event. By adopting the method, the accuracy of apnea detection during sleep can be improved.

The invention provides a sleep apnea monitoring method, device and equipment and a storage medium. According to the sleep apnea monitoring method and device, shallow and deep physiological data are captured through multiple wavelength signals corresponding to multiple light sources, and blood oxygen signals are obtained through the obtained physiological data; then, analyzing local features and different weights of various physiological data and blood oxygen signals to obtain global features representing a change time sequence of a sleep breathing event of the user, and judging whether the user has a hypopnea event or not by analyzing continuous fragment features of a first preset duration in the global features; according to the scheme, whether the hypoventilation event is accurate or not is verified again in a mode of secondary confirmation of the abnormal signals according to the condition that whether the hypoventilation event occurs or not and whether continuous abnormal signals still occur or not after the hypoventilation event occurs, and the scheme can be completed through the wearable equipment, so that the equipment has the advantages of miniaturization, low power consumption and low cost; and the technical scheme is obtained through comprehensive analysis of various data, so that the accuracy of the result can be improved.

The invention relates to the technical field of signal processing, in particular to a vital sign risk assessment method for ballistocardiogram signals, which comprises the following steps of: calculating heart rate index data, sleep quality index data and sleep apnea index data based on the ballistocardiogram signals and respiratory effort signals acquired in a user monitoring process; the vital sign risk assessment method and device are used for performing vital sign risk assessment and improving the accuracy and efficiency of vital sign risk assessment.

The application discloses an obstructive sleep apnea device and method; the device comprises a mouthpiece carrier, an electrode stimulation module and a control unit, the electrode stimulation module comprises an integrated flexible circuit board transmission link, the transmission link is integrated with a stimulation electrode with a nickel-titanium alloy support strip on the inner side of the mouthpiece carrier, and the stimulation electrode can apply electric stimulation to the genioglossus muscle or hypoglossal nerve; the external control unit is provided with a microcontroller and an acoustic sensor; the method first collects an environmental background signal, processes the signal to generate a signal determination threshold, then collects a human respiratory acoustic vibration signal in real time, processes the signal to generate a respiratory sound energy value, compares the two to determine an abnormal respiratory event; after determining the abnormality, a gradient output electric stimulation is output, and a dynamic feedback mechanism is combined to adjust the stimulation intensity; when the stimulation intensity is zero and there is no abnormal signal, it is determined that the intervention is completed and the standby state is entered; the application can adapt to environmental noise, avoid current mutation discomfort, closed-loop control intervention intensity, and is suitable for sleep apnea auxiliary intervention.

Described herein are systems and methods for characterizing a subject's ejection fraction (EF) status, heart failure status, and / or sleep apnea status. In particular, described herein are systems and methods for characterizing a subject's EF status, heart failure status, and / or sleep apnea status through use of a wearable electrocardiogram (ECG) device having LII and LIII leads, and software configured to incorporate data from the ECG device and assess the subject's EF status, heart failure status, and / or sleep apnea status.

The invention discloses a sleep apnea regulation and control system based on a time interference array electrode, and relates to the technical field of medical instruments. The system comprises an electrical stimulation controller and an array electrode, the array electrode comprises a plurality of electrode points, and the electrode points are configured to be paired in pairs to form a plurality of stimulation channels; the electrical stimulation controller comprises a time parameter obtaining module used for obtaining time parameters, an electrical stimulation parameter obtaining module used for obtaining electrical stimulation parameters and a control module, and the control module is used for generating and regulating electrical stimulation signals of all channels according to the electrical stimulation parameters. According to the time parameter, controlling the output and stop of the electrical stimulation signal of each channel; and the electrical stimulation module is further configured to output the electrical stimulation signals of the channels to the array electrode. The system provided by the invention realizes time interference focusing electrical stimulation and closed-loop control thereof. The problems that in the prior art, percutaneous electrical stimulation is poor in precision, sleep awakening is easily caused, and parameter titration is difficult are solved.

Techniques for automated titration of CPAP device for a subject include receiving multiple ultrasound images representing a cross section of an airway in a neck of the subject at corresponding different times. Multiple different positive pressure values imposed by a device on the airway of the subject are also received at each of the corresponding times. For each of the ultrasound images, a mask of pixels associated with an air-tissue interface is automatically formed, and a value of a statistic of pixels within the mask is automatically determined. A titration pressure for a continuous positive airway pressure (CPAP) device is automatically determined based on the positive pressures and the value of the statistic for each of the ultrasound images. Output data that indicates the titration pressure for the CPAP device is presented on a display device, such as by operating the CPAP device itself at the titration pressure.

Wearable devices are provided herein including wearable defibrillators, wearable devices for diagnosing symptoms associated with sleep apnea, and wearable devices for diagnosing symptoms associated with heart failure. The wearable external defibrillators can include a plurality of ECG sensing electrodes and a first defibrillator electrode pad and a second defibrillator electrode pad. The ECG sensing electrodes and the defibrillator electrode pads are configured for long term wear. Methods are also provided for using the wearable external defibrillators to analyze cardiac signals of the wearer and to provide an electrical shock if a treatable arrhythmia is detected. Methods are also disclosed for refurbishing wearable defibrillators. Methods of using wearable devices for diagnosing symptoms associated with sleep apnea and for diagnosing symptoms associated with heart failure are also provided.

The present technology generally relates to methods for addressing sleep apnea in a patient. At least some of the methods may include one or more of percutaneously inserting an implantable signal delivery device at an insertion point on a patient's neck, moving the signal delivery device in a medial-to-lateral direction toward a neck loop nerve of the patient, and implanting the signal delivery device at a target location at least proximate the neck loop nerve. The signal delivery device may include at least one electrode positioned to deliver a modulation signal to tissue, such as a portion of a neck loop nerve, at least proximate to a target location. In some embodiments, delivery of the modulation signal may induce a patient's trailing-side traction, thereby addressing sleep apnea in the patient.

This application relates to the field of sleep monitoring technology, providing a method, system, device, medium, and product for sleep apnea identification. The method includes: acquiring multimodal sensing data; acquiring sleep state identification information based on the multimodal sensing data; determining that the user is asleep based on the sleep state identification information; and acquiring sleep breathing analysis information based on the sleep state identification information and the multimodal sensing data. Multimodal sensing data can comprehensively and multidimensionally capture physiological data related to sleep apnea, improving the accuracy of sleep apnea identification. Before performing apnea analysis, it first identifies whether the user is asleep; apnea identification processing is only performed when the user is asleep. Apnea identification processing is unnecessary when the user is awake, avoiding continuous complex analysis and reducing power consumption. The two-layer processing of first identifying the sleep state and then identifying apnea improves interpretability.

A device may include: a bed. A sensor may be configured to configured to: sense pressure applied to the bed; and transmit a pressure stream. A plurality of temperature sensors arranged across the bed can be configured to: sense temperature in a particular location of the bed; and transmit a datastream of the sensed temperature. A computing system comprising can be configured to: receive the pressure stream; receive each of the datastreams; identify an apnea event; generate a sequence of heart rate values for the user for cardiac activity; generate a sequence of skin temperature values for the user; determine a change in heart rate; determine a change in skin temperature within the second time window; determine a relationship between the change in heart rate and the change in skin temperature; and determine a severity score for the apnea event based on the relationship.

An oral appliance (10) for treating sleep apnea in a user, comprising a dental tray (20) configured to be placed in the oral cavity of the user, a processor, and at least one sensor coupled to the dental tray. According to an aspect, the processor can be configured to detect a condition of the user based on data generated by the at least one sensor. Further, the sensor can comprise at least one of a sound measuring device, an inertial measurement unit, a pulse oximeter, or an electroencephalogram.

The present disclosure relates to a device (100) for the treatment and / or prevention and / or testing of bruxism or craniomandibular dysfunction, sleep apnea and other parafunctional movements such as tongue thrusting, which is designed to be arranged between the upper and lower jaw of a user in a dental appliance or to form a dental appliance, the device comprising a biofeedback unit, in particular a mechanism as a simultaneous sensor and feedback transmitter for biofeedback or in particular a mechanism,which, upon reaching a predetermined threshold of jaw movement and / or the force resulting from a jaw movement, snaps from a first state to a second state with a switching behavior, generating feedback to the user via one or more of the human senses, and returns to the first state when the force from the jaw movement ceases, or a sensor offset towards the occlusal surfaces, or an arrangement in a section of a mandibular occlusal splint that spans or bridges the legs (bridging section). Further devices and methods for manufacturing are also disclosed.

Breathing mask for use with CPAP or ventilators, including: • an integrated nasal applicator with two conically shaped pads that can be inserted into the nostrils, • a central connecting element made of flexible, biocompatible material, • wherein the nasal cushions are connected to each other by a bridge to prevent complete penetration into the nose, • and wherein the mask has a front port for a breathing tube and a rear port for a mouthpiece.

The utility model discloses a sleep apnea treatment mask carbon dioxide rebreathing tester which comprises a device body, the device body comprises an equipment cabinet body, a human head model, a carbon dioxide rebreathing tester and a display screen, and the carbon dioxide rebreathing tester and the display screen are both installed on the left side of the front end of the equipment cabinet body. The carbon dioxide rebreathing tester is positioned on the lower side of the display screen; a test storage bin is formed in the right side of the front end of the equipment cabinet body and is of a rectangular structure, a test mounting column is arranged in the test storage bin and is of a cylindrical structure, a model mounting table is arranged at the top of the test mounting column, the head model is mounted at the top of the model mounting table, and a test door is mounted on the outer side of the test storage bin through a hinge. The surface of the test door is provided with an observation window. According to the device, a space for detecting the sleep apnea treatment mask can be provided, and the sleep apnea treatment mask can be conveniently detected.

The application discloses a sleep apnea monitoring system based on non-contact intervention and belongs to the technical field of medical health monitoring.The application solves the problems of the PSG method in the prior art, such as complicated operation, high cost, and the discomfort brought to users by household contact devices, and influences natural sleep, physiological signals are collected by a non-contact biological radar sensor, an optimal threshold is calculated by comprehensively considering an initial threshold, an auxiliary threshold and environmental factors, and the accuracy of apnea and hypopnea event detection is improved, in combination with an apnea hypopnea index, an event duration factor, a blood oxygen drop factor and an event type factor, a severity score is calculated, patients are divided into mild, moderate and severe, according to the severity, grade and snoring sound category of real-time events, an optimal intervention measure is selected from an intervention strategy library, individualized intervention is realized, the interference on patient sleep is reduced, and the sleep quality and life quality are improved.

The application discloses a sleep apnea type distinguishing method and device based on a millimeter wave radar and a computer readable storage medium, and the method comprises the following steps: acquiring a millimeter wave radar echo signal of a monitoring object in a monitoring area; extracting a body movement signal feature, a chest cavity reflection signal energy feature and a breathing signal amplitude feature from the echo signal; constructing a time sequence feature sequence based on the extracted body movement signal feature, the chest cavity reflection signal energy feature and the breathing signal amplitude feature; inputting the feature sequence into a pre-trained classification model based on a self-attention mechanism to perform dynamic correlation analysis, and determining a sleep apnea type of the monitoring object. The application has the advantages of non-contact and accurate sleep apnea type distinguishing.

The application relates to an auxiliary device, which comprises an upper support and a lower support, the upper support and the lower support are movably connected, the upper support comprises a forehead air bag adjusting box (1) and upper two side support connecting arms (2), the forehead air bag adjusting box (1) is rotatably connected with the connecting arms (2), the lower support comprises a lower support connecting plate (3) and two support bows (4), a neck stabilizing adjusting belt (5) is arranged between the support bows (4), a front chest adjusting air bag (6) is arranged on the connecting plate (3), an adjusting air bag quick connecting joint (12) is arranged on the front chest adjusting air bag (6), the connecting plate (3) and the support bow (4) are movably connected, the sleep apnea eliminating device further comprises an air bag adjusting hand pump, and the air bag adjusting hand pump is movably connected with the adjusting air bag quick connecting joint (12). The application belongs to the technical field of external physical devices for eliminating sleep apnea diseases.

A method for treating sleep apnea provides an implantable device having at least one layer of piezoelectric material sandwiched by an outer electrode and an inner electrode, implanting the implantable device inside the tongue of a patient, and generating electricity when the implantable device deforms, such that the electricity flows to the hyoglossus nerve to stimulate it, thereby moving the tongue to open the upper airway of the patient.

The present technology is generally directed to methods for addressing a patient's sleep apnea. In some embodiments, the method includes identifying one or more locations or sites at which the patient experiences tissue collapse, using the identified tissue collapse sites to select one or more target tissues associated with this tissue collapse, and positioning one or more signal delivery devices to deliver modulation signals to the one or more target tissues.

The application provides a sleep apnea detection method and a detection device, and relates to the technical field of respiration detection. The method comprises the following steps: extracting physiological signals under each channel from a polysomnogram in a detection period, dividing the detection period according to a preset time to obtain a plurality of time segments; determining a signal identifier corresponding to each physiological signal, and dividing each physiological signal according to the signal identifier to determine a first signal type and a second signal type; for each time segment, inputting the physiological signals corresponding to the first signal type of the time segment into a first sleep apnea detection model to obtain a first set, and inputting the physiological signals corresponding to the second signal type of the time segment into a second sleep apnea detection model to obtain a second set; and identifying the proportion of patients with apnea based on the first set and the second set. Through the application, the plurality of physiological signals are processed, and the accuracy of the sleep apnea result is improved.

Systems and methods for monitoring and staging sleep using cardiac and respiratory information are disclosed. An exemplary system includes a storage device to store a trained hybrid sleep detection and classification model, the model including a plurality of trained machine learning models, each model trained to map input cardiac and respiratory data to one of a plurality of different model-specific awake or sleep categories, and a trained regression model for combining the model-specific awake or sleep categories into a composite awake or sleep classification. A sleep detector applies cardiac and respiratory information of the patient to the trained hybrid sleep detection and classification model to determine a composite awake or sleep classification for the patient. Composite waking or sleep classification is used to diagnose medical conditions, including sleep apnea.