115 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 invention belongs to the technical field of medical signal processing, and discloses a sleep apnea detection method and system, electronic equipment and a storage medium, and the method comprises the following steps: obtaining synchronous ECG signals and respiratory signals, and processing the signals into bimodal data fragments containing a plurality of time scales; a parallel neural network architecture is constructed, ECG features and respiratory signal features are extracted from the data segments of all scales, and cross-modal feature pairs are formed; designing a cross-scale dynamic weight correction attention mechanism, and carrying out dynamic weighting and information fusion on cross-modal feature pairs among different scales by introducing a correction factor based on an Euclidean distance among feature vectors so as to enhance the relevance between local details and a global context; and inputting the fused multi-scale features into a classifier, and outputting the probability of the sleep apnea event. Through multi-scale collaborative analysis and a dynamic weight correction attention mechanism, physiological information of different time dimensions is effectively fused, and the detection accuracy is improved.

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 present invention discloses a sleep apnea monitoring method, comprising: acquiring EEG signals, EOG signals, and photoplethysmography signals; automatically staging sleep and calculating sleep duration based on the EEG and EOG signals; counting apnea and hypopnea events based on the photoplethysmography signals; and calculating the AHI index based on the calculated sleep duration (ST) and the number of apnea and hypopnea events (BSN). Furthermore, a corresponding head-mounted sleep apnea monitoring system and electronic device are also disclosed. The present invention enables real-time and accurate sleep staging and apnea diagnosis.

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.

Introduced are methods and systems for monitoring a person's sleeping patterns, and detecting episodes of sleeping disorders such as snoring and sleep apnea. In one embodiment, a sensor strip attached to the mattress monitors the user's breathing, and detects signature frequencies corresponding to snoring and sleep apnea. Once a sleeping disorder is detected, a notification can be sent to a device associated with the user, or the user's bed can be automatically adjusted to alleviate the sleeping disorder.

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.

A system and method for monitoring sleep apnea in cancer patients undergoing treatment are disclosed. The system includes a device to collect SpO2 signals from a patient over multiple sleep sessions, a gateway to receive and process the SpO2 signals to generate formatted SpO2 data, an apnea monitoring service to determine an apnea measure based on the formatted SpO2 data, and a user service to provide a longitudinal progression of the apnea measure. The method involves collecting SpO2 signals, processing them at a gateway, determining an apnea measure, and providing a longitudinal progression of the apnea measure over multiple sleep sessions. The system and method enable efficient monitoring and analysis of sleep apnea in cancer patients during treatment.

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.

Reminder of the titleDevice for sleeping with a medical device by Continuous Positive Pressure used for the treatment of sleep apnea. Technical field and statement of the problemThe invention relates to a device for sleeping with a CPAP device without risk of air leakage and removal of the mask. Main characteristics of the solutionIt consists of a T-shirt (1) or a nightie having on its front face a funnel-shaped pocket (2), equipped with a zipper (4) through which the air tube (6) is introduced to keep it in line with the patient's mask (7). Thus, during movements during sleep, the patient moves his mask and the air tube simultaneously in the same direction, canceling any friction force. Intended useThe device according to the invention is particularly intended for better patient acceptance of his Continuous Positive Pressure ventilation treatment.Choice of an illustration to accompany the abstractFigures for the abstract: Fig.1, Fig.2.

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.

Device to combat sleep apnea Reflexogenic orthosis regulating the aeroelasticity of the pharynx FIGURES

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.

The invention relates to the technical field of respiration monitoring, in particular to a snore monitoring method and device for sleep apnea pathology identification. The method comprises the following steps: acquiring an infrared grayscale image and a breathing audio signal; determining a temperature expression value according to the gray level change of two continuous frames of infrared gray level images; analyzing to obtain inspiration duration and expiration duration; further determining the breathing depth of each actual breathing interval; then, according to the breathing audio signals of the intersection point of the inspiration process and the expiration process and the two end points on each actual breathing interval time sequence, an initial estimation audio signal is determined; further determining a snore signal and a noise signal, and determining the breathing change intensity of each actual breathing interval according to the amplitude change and breathing depth of all extreme points in the snore signal; according to the breathing change intensity, whether each actual breathing interval is abnormal snore or not is determined. The abnormal snore monitoring accuracy and reliability are improved.

The invention discloses a head-mounted monitoring device for sleep apnea treatment, which belongs to the technical field of sleep monitoring and is characterized in that a certain pressure is applied to a throat airflow voiceprint monitoring module and a nasopharyngeal cavity pressure wave dynamic monitoring module under the action of a torsional spring to prevent the throat airflow voiceprint monitoring module and the nasopharyngeal cavity pressure wave dynamic monitoring module from deviating from a monitoring area at the neck; a flexible supporting mode does not hurt a patient, a rotating base is supported through the elastic force of a second spring, due to the fact that the skin is dragged at different angles when the neck moves, a rotating disc can rotate in a sliding barrel, a rubber arc plate can be adjusted in a self-adaptive mode according to the dragging angle of the skin, and therefore the patient can be more comfortable. The neck of the patient is roughly arc-shaped, so that the middle part of the outer side of the rubber arc plate deflects around the end part of the rotating seat through the pin shaft after the rubber arc plate horizontally moves for a certain distance, and the inner side of the rubber arc plate can be fully attached to the skin at the neck; and the monitoring precision is improved.

A noise-reducing respiratory device configured to improve or treat respiratory system-related disorders such as sleep apnea. The device includes a noise-reducing gas passage located inside a casing of the device, and is connected to the casing. The casing of the respiratory device also has at least one air intake and at least one air outlet. The air intake is configured to receive breathable gas into the chambers of the noise-reducing gas passage. The air outlet is configured on one side to communicate with an outlet of the blower, and on the other side, it connects to a breathing hose. Additionally, electronic components and a soundproofing material are provided between the noise-reducing gas passage and the casing of the device. Furthermore, there is no foam present where the internal gas flows through the respiratory device.