95 results about "Sleep analysis" patented technology

The present invention is both a device and a method for verifying a subject's identity while using a medical device or undergoing a medical diagnostic or therapeutic procedure, particularly at home or at a remote location. The method and device can be used for inpatient and remote sleep and signal analysis with biometric identification. The present invention is further related to the devices and sensors used in executing the method, and includes various embodiments of a method of inpatient and remote sleep analysis.

The invention provides a sleep analysis system and a method for analysis thereof. The sleep analysis system includes an analysis device and a sleep sensing apparatus. The sleep sensing apparatus includes an ECG signal collector, a multi-axial accelerometer, a wireless transmitting unit, and a control unit. The ECG signal collector is used for collecting an ECG signal associated with a subject. The multi-axial accelerometer is used for detecting a multi-axial accelerometer signal associated with the subject. The control unit controls the wireless transmitting unit to transmit the ECG signal and the multi-axial accelerometer signal to the analysis device for analyzing sleep of the subject.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

The invention belongs to the technical field of sleep monitoring, and particularly relates to an intelligent sensing mattress for monitoring sleep. Two kinds of flexible pressure sensors are adopted, wherein the first kind of the pressure sensors are used for producing pressure sensing arrays, are uniformly distributed in the whole mattress, and are used for detecting stressing conditions in the most part of the mattress, the second kind of sensors are distributed in several key positions of the mattress, and are used for collecting signals which can cause pressure change like respiration signals, body movement signals, and heart rhythm signals of a user, and transferring the pressure changing signals into electric signals; follow-up hardware conducts amplification, smoothing and transmission on the obtained electric signals, then conducts feature extraction and pattern recognition processing on the signals through a PC end to obtain a pressure distribution image and sleep analysis. According to the intelligent sensing mattress for monitoring sleep, ultra-thin flexible materials are used in sensors and structures thereof like electrodes, thus the mattress is small in thickness, light in weight, and convenient to carry; due to the fact that the intelligent sensing mattress for monitoring sleep is run in a non-intrusive mode, sleep monitoring can be conducted under the condition that a user is unconscious, thus the natural sleep of the user can be fully restored, and thus powerful supplement is made for family-type nursing.

Apparatus for providing transcutaneous electrical nerve stimulation (TENS) therapy to a user, the apparatus comprising: a housing; an application unit for providing mechanical coupling between the housing and the user's body; a stimulation unit for electrically stimulating at least one nerve of the user; a sensing unit for sensing the user's body movement and body orientation; and a reporting unit for providing the user with feedback based on the user's sensed body movement and body orientation.

The invention discloses a sleep analysis method and device. The method includes the steps that multi-axis accelerated speed data collected within each subsidiary monitoring period of a person to be monitored are acquired according to the preset sampling frequency; based on the multi-axis accelerated speed data collected within each subsidiary monitoring period of the person to be monitored, the activity of the person to be monitored within each subsidiary monitoring period is determined; for each subsidiary monitoring period, according to the activity in a subsidiary monitoring period included in a period window corresponding to the subsidiary monitoring period, the activity characteristic value of the person to be monitored within each subsidiary monitoring period is determined, and a dynamic threshold value of the activity characteristic value within the monitoring period is determined as well; the activity characteristic value within each subsidiary monitoring period is compared with the dynamic threshold value, so that a first sleep analysis result of the person to be monitored in a sleeping state or a waking state within each subsidiary monitoring period is acquired. By the adoption of the method, waking and sleeping classification accuracy is improved.

The invention provides a sleeping control device and method. The device at least comprises a mobile side, a detector and a cloud side server, is used for determining theoretical sleeping state information corresponding to body signals based on a preset database through a sleeping analysis algorithm, and is characterized in that the cloud side server completes the correction and demonstration process of the theoretical sleeping state information on the basis of the before-sleeping feeling, after-sleeping feeling, actual sleeping state information and/or external condition information input by the user through the mobile side, and the mobile side is configured to retrieve the actual sleeping state information and related information stored in the cloud side server and/or the mobile side through self-definition keywords, external conditions and/or physical features by the user. By making the sleeping feeling of the user related to the actual sleeping state of the user, the personalized sleeping state guiding can be more effectively conducted, and the ability of controlling the sleeping state by the user is trained and improved.

An embodiment of the invention discloses an electroencephalogram processing apparatus and method and a sleep monitoring worn device and relates to the technical field of electronics. The electroencephalogram processing apparatus and method and the sleep monitoring worn device can reduce the complexity of sleep stage classification. The electroencephalogram processing method includes the steps of obtaining electroencephalogram data to be processed; obtaining the predetermined number of segments from the electroencephalogram data to be processed, wherein the segments do not overlap; obtaining a maximum value and a minimum value of peak-to-peak values of every segment; normalizing the connection line between the maximum value and the minimum value of the peak-to-peak values of at least one of the segments to obtain an upper end point and a lower end point of the connection line; calculating a statistical characteristic value of an upper side band curve formed by the upper end points to obtain a box plot sequence; obtaining a sleep stage classification result according to the box plot sequence. The electroencephalogram processing apparatus and method and the sleep monitoring worn device are applicable to sleep analysis.

The invention is applicable to the technical field of smart home, and a sleep monitoring system and a sleep monitoring method based on the sleep monitoring system are provided. The sleep monitoring system includes a bed and a monitoring device connected to the bed, the bed comprises a piezoelectric thin film sensor for collecting physiological state information of a user lying on the bed and sleepinformation of the user while sleeping, an acoustic sensor for collecting snoring sound emitted by the user while sleeping, and a motor for controlling the head of the bed to rise or fall under the control of a monitoring device. The monitor device is used for determining whether the user enters a sleep state according to the physiological state information, and is used for analyzing the sleep quality of the user according to the sleep information and the snoring sound to obtain the corresponding sleep analysis result, and controlling the bed head to rise or fall according to the sleep analysis result, thereby improving the monitoring effect and simplifying the sleep monitoring system, which can be better used by the ordinary user, and further improving the user experience.

The invention relates to the technical field of intelligent home, and particularly discloses an intelligent home sleep device. Wherein the device comprises a piece of sleep furniture and a sleep control device mounted on the sleep furniture, the sleep control device comprises a signal acquisition module, an intelligent control module and a sleep induction module, the signal acquisition module is in communication connection with the intelligent control module, and the intelligent control module is in communication connection with the sleep induction; the signal acquisition module is used for acquiring human sleep data; the intelligent control module is respectively used for performing data processing on environmental data and sleep data so as to obtain sleep control signals, analyzing sleepdata so as to obtain sleep analysis results and transmit the sleep analysis results to a terminal server; and the sleep induction module is used for adjusting configuration information of the sleep furniture according to the sleep control signals. The invention also discloses an intelligent home sleep system. The intelligent home sleep device can assist people to fall asleep as soon as possible.

An appearance ratio conversion processing portion 103 reads sleeping depth data (qualitative variable) stored in a RAM 102 to calculate a movement appearance ratio n-M.A.R. (quantitative variable) meeting a relation of sleeping depth >= 2 (slow wave sleep: SWS). Then, an evaluation result calculation processing portion 104 reads the movement appearance ratio data (quantitative variable) of the calculated SWS from the RAM 102, and processes the calculated movement appearance ratio data in accordance with an evaluation rule in an evaluation rule storage portion 105 to calculate an evaluation score for an evaluation factor. When the evaluation factor is 'easy sleep' for example, a time period from a point when a person goes to bed to a point when the movement appearance ratio n-M.A.R. of the SWS rises is detected from the movement appearance ratio n-M.A.R. of the SWS. Then, an evaluation score corresponding to a length of a time period of the rising is acquired from a corresponding score table. Sleep analysis with relatively high reliability can be simply and speedily performed by using sleeping depth data.

Systems and methods are provided for monitoring a person's sleeping activities in a dwelling. A detection device is in communication with a user monitoring device. The detection device includes at least one motion/movement gesture sensing device configured to detect at least one of a person's motion, movement and gesture. A user monitoring device includes at least one element selected from: a proximity sensor; a temperature sensor; a humidity sensor; a particulate sensor; a light sensor; a microphone; one or more RF transmitters (BLE/ANT+WIFI); a memory; and one or more LED's. An amount of night and noise is detected in the vicinity of the person.

The present application relates to a sleep quality monitoring method, system, computer device and storage medium. The method includes: receiving a first monitoring instruction sent by a monitoring device, and entering a first mode according to the first monitoring instruction; in the first mode, collecting a first sleep parameter of the monitored object; in the first mode, sending a first synchronization instruction to the sleep aid device, and receiving a second sleep of the monitored object returned by the sleep aid device according to the first synchronization instruction parameter; obtaining a preset sleep analysis model, inputting the first sleep parameter and the second sleep parameter into the sleep analysis model to obtain sleep data of the monitored object; the sleep data is sentto the monitoring device, and the monitoring device analyzes the sleep data and analyzes the data corresponding to the sleep quality of the monitored object. This method can improve the accuracy of sleep quality monitoring.

The invention discloses a sleep analysis system. The system comprises a mobile terminal and a cloud platform. The mobile terminal is used for detecting sound information when a user sleeps, extracting characteristic information in the sound information by using a sound identification technology and sending the characteristic information to the cloud platform. The sound information comprises a user sleep sound and an environment noise. The cloud platform is used for receiving the characteristic information, and inquiring a preset voice database according to the characteristic information to acquire sleep guidance information corresponding to the user. In the invention, a microphone of an existing mobile terminal is used to detect the sound information when the user sleeps; a sound identification technology is used to extract the characteristic information, and the characteristic information is classified and then is analyzed through cloud platform mass data so that specific sleep guidance is performed on the user. Simultaneously, the cloud platform also provides an intelligent wake-up service.

The invention discloses an electroencephalogram stimulation memory enhancement system based on portable EEG equipment. The system comprises four parts of a specially-made EEG electroencephalogram stimulator, a specially-made EEG signal analysis system, a sleep analysis algorithm and a specially-made electric wave stimulation manner. A working principle of the system lies in that: the specially-made EEG electroencephalogram stimulator collects brain waves of a user during sleeping and transmits the brain waves to the specially-made EEG signal analysis system in real time; the analysis system decodes and preprocesses EEG signals, and judges the sleep stage of the user through a machine learning algorithm; when the user enters a rapid eye movement sleep stage, a stimulation instruction is sent to the stimulator for electric wave stimulation, and the brain memory function is enhanced; and when the user enters a non-rapid eye movement sleep stage, sending the stimulation instruction is stopped, and electric wave stimulation is stopped. According to the method, data characteristics of sleep EEG signals are analyzed, and a principle that slow wave frequency electroencephalogram stimulation during sleep can promote synchronization of specific neurons (ABNs), and enhance the memory, is adopted, and the function of enhancing brain memory during sleep is achieved.

The invention relates to a sleep monitoring method. The sleep monitoring method comprises the steps of obtaining real-time sleep data, wherein the real-time sleep data comprises real-time electroencephalogram signal data and real-time human body physiological sign data; obtaining historical sleep data, wherein the historical sleep data are stored in a database, and the historical sleep data comprises historical electroencephalogram signal data and historical human body physiological sign data; and generating a sleep analysis report based on the real-time sleep data and the historical sleep data, wherein the sleep analysis report at least comprises a sleep evaluation result and a physiological data monitoring result. By means of the sleep monitoring method, the problems that during sleep monitoring, only a brain wave monitoring device exists, reference data are few, and the current body sleep condition is difficult to recognize more clearly are solved, and the technical effect that when sleep is monitored, the brain wave data and the human body physiological sign data can be referred to, so that the accuracy of sleep monitoring state judgment is improved is achieved.