213results about "User/patient communication for diagnostics" patented technology

The invention discloses a multi-modal data fusion and intelligent analysis high-precision sleep monitoring system and method. The system comprises a data acquisition layer, a transmission layer, an analysis layer and an application layer, the data acquisition layer transmits data acquired by a sensor to the transmission layer step by step through BLE or Wi-Fi, the transmission layer divides the data acquired by the sensor into two paths through a Wi-Fi module and transmits the data to a main control device and a cloud server in the analysis layer, and the main control device and the cloud server process the data. The data collection layer comprises a data collection module, the data collection module comprises a physiological data collection unit, an environment data collection unit and a subjective data collection unit, the data collection layer is used for collecting data of multiple sources such as physiological data, environment data and subjective data, and the data collection layer is used for collecting data of multiple sources such as the physiological data, the environment data and the subjective data. The deep learning and big data analysis technology is applied, high-precision recognition of the sleep state and precise evaluation of health risks are achieved, and a personalized sleep improvement scheme is provided.

Systems and methods for predicting problem behavior in individuals with developmental and behavior disabilities. A plurality of sensors are configured to collect multimodal data signals of a subject individual including a wearable upper body motion sensing device with a plurality of inertial measurement units (IMUs). An electronic controller is configured to receive output signals from each of IMUs and to model an upper body position of the subject individual based on the output signals from the IMUs. A trained machine-learning model is then applied by providing an input data set that includes multimodal signal data (e.g., including signal data from at least one IMU) and / or features extracted from the multimodal signal data. The machine-learning model is trained to produce as output an indication of whether a precursor to the problem behavior is detected and, in response to detecting the precursor, a notification (or alarm) is generated.

The invention relates to the technical field of medical data analysis and rehabilitation, in particular to a cerebral apoplexy patient rehabilitation exercise analysis system based on medical big data, which comprises a data acquisition module used for acquiring electromyographic signals, exercise data and behavior data of a patient to form a data set; the data processing and fusion module is used for preprocessing the electromyographic signals in the data set, normalizing motion and behavior data and fusing the motion and behavior data into a multi-modal feature vector; the hierarchical analysis module is used for performing motion intention recognition according to the preprocessed electromyographic signals and outputting an intention classification result, recognizing the motion intention and predicting a rehabilitation effect through a double-flow Transform encoder, and evaluating a behavior risk level in combination with a risk factor formula; the optimization module is used for dynamically adjusting the mirror image treatment intensity according to the risk level and optimizing the prediction model by adopting incremental learning; and the interaction module is used for generating a thermodynamic diagram superposition rehabilitation curve in the X-Y coordinate system, and marking doctor intervention suggestions to complete visual interaction.

The invention discloses portable intelligent assessment and rehabilitation training integrated equipment for cognitive disorder patients, and belongs to the technical field of cognitive disorder assessment. Comprising a device body composed of a base and a display screen, and the device body is electrically connected with an intelligent evaluation training system. The problem that an existing assessment method has limitation is solved, and the portability of existing medical equipment is improved by performing integrated design on the equipment in a notebook computer form; multi-dimensional evaluation data of the patient are collected through a MoCA Monte-Evaluation scale, scores and change trends of all cognitive functions are extracted by using a correlation analysis method, and the scores and change trends are predicted through a neural network model to obtain a prediction result of the patient; corresponding rehabilitation training suggestions are retrieved from the decision tree classification model, optimization is carried out in combination with actual conditions, and then rehabilitation training is carried out on the patient; and by introducing an intelligent technology, personalized design and comprehensive intervention, the evaluation and rehabilitation training effects are further improved.

The invention relates to the technical field of blood glucose monitoring, in particular to an intelligent blood glucose monitoring and early warning method and system based on multi-source data fusion. Comprising the following steps: S1, acquiring blood glucose monitoring information of a monitored object, and determining first combined blood glucose monitoring information and second combined blood glucose monitoring information according to the blood glucose monitoring information; the first combined blood glucose monitoring information is an absolute difference between the blood glucose instantaneous information and the blood glucose continuous information; the second combined blood glucose monitoring information is a mean value of the blood glucose instantaneous information and the blood glucose continuous information; acquiring environment information of the monitored object, and determining a first environment variable quantity and a second environment variable quantity according to the environment information. According to the method, the dynamic deviation parameter and the early warning threshold value are fused, the measurement deviation and the physiological delay are quantified in combination with the extreme value features, double-source interference suppression and individualized early warning optimization of blood glucose monitoring are achieved in the plateau environment, and the risk identification accuracy and adaptability are improved.

A vagus nerve stimulation system for stimulating a vagus nerve in a biological subject, the system including a clip configured to be attached to a tragus of the subject, the clip including opposing arms configured so that a distal end of the arms are biased towards each other and electrodes positioned proximate a distal end of the arms on opposing faces so that the electrodes are urged into engagement with opposing faces of the tragus and a signal generator electrically connected to the electrodes, the signal generator being configured to generate at least one therapy signal that is applied to the vagus nerve within the tragus via the electrodes, to thereby modulate the vagus nerve.

A computing device for enhancing communications is disclosed. The computing device includes a memory configured to store data, a video camera configured to receive video input data, and a microphone configured to receive audio input data. The computing device also includes a processor that is configured to analyze the received video input data, the received audio input data, and the data stored in the memory. The computing device further includes a visual display device that is configured to output a visual display based on the processor analysis, and a speaker output device that is configured to output an audio signal based on the processor analysis.

One embodiment may provide a method of providing a notification of signal loss in a glucose monitoring system, the method including, when a communication failure occurs between a terminal and a sensor transmitter, delaying a signal loss notification for a first period of time by the terminal, when the communication failure persists for the first period of time, further determining whether signal loss persists for a second period of time by the terminal, when the signal loss persists for the second period of time, generating the signal loss notification by the terminal, and outputting, by the terminal, the signal loss notification to a user.

The invention discloses a multi-modal sensing data automatic labeling method and system for gait assessment, and the system comprises a sensing collection module which comprises two paths of pressure sensors and a six-axis IMU sensor; the two paths of pressure sensors are used for acquiring plantar pressure data; the six-axis IMU sensor is used for acquiring lower limb movement data; the wireless transmission module is used for uploading the collected plantar pressure data and lower limb movement data to a cloud Internet of Things platform; the cloud data processing module is used for receiving and storing the plantar pressure data and the lower limb movement data; the data labeling module is used for automatically recognizing a gait cycle and carrying out multi-dimensional score labeling; and the user interaction module is used for interacting with the data annotation module and the cloud data processing module and displaying gait evaluation related data and results. According to the invention, a multi-mode sensing PCB is self-developed, a closed-loop system of collection, cloud loading, labeling and display is constructed, and accurate, continuous and remote evaluation of gaits of children with cerebral palsy is realized.

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 provides an activity level evaluation method and related equipment, and belongs to the technical field of terminals. The method comprises the following steps: screening a first heart rate of a user under low activity intensity and a second heart rate of the user under medium and high activity intensity according to walking heart rates in heart rate data of the user in the past one week; acquiring a weekly activity level assessment result of the user according to the first heart rate and the second heart rate by using an activity level assessment hierarchical model, the activity level assessment hierarchical model including a first activity level assessment model corresponding to low activity intensity and a second activity level assessment model corresponding to medium and high activity intensity, the activity acquisition module is used for acquiring the corresponding activity amount according to the heart rate, and the unit of the activity amount is Meide MET multiplied by time. According to the method, an activity level analysis result of a user is obtained by taking weekly activity data as an analysis unit through a personalized hierarchical model, so that the problem that an activity level evaluation result cannot be in butt joint with an international standard and is inaccurate is solved.

A system for determining placement of a catheter in a patient includes a hemodynamic sensor and a display. The hemodynamic sensor produces a signal representative of a right ventricular pressure waveform of the patient. The catheter is connected to the hemodynamic sensor. The system further includes one or more processors and computer-readable memory encoded with instructions that, when executed by the one or more processors, cause the system to receive the signal representative of the right ventricular pressure waveform and extract features from the right ventricular pressure waveform. The instructions further cause the system to compare the features to one or more value ranges of the features to determine that the catheter is correctly placed when values of the features are within the one or more value ranges or that the catheter is incorrectly placed, is not properly connected to the system, or signal quality issues are occurring.

The present invention refers to a respiratory therapy device comprising: a mouthpiece defining a longitudinal axis and having an end port; a housing connected to the mouthpiece and having a top surface, wherein at least a portion of the top surface is longitudinally spaced from the end port and defines a viewing surface adapted to be visible to a user having the end port disposed in a mouth of the user; and a feedback array disposed on the viewing surface, wherein the feedback array extends diagonally across the viewing surface and is curved or curvi-linear.

An air adapter tube for diagnosis and / or treatment of a respiratory disorder includes a tubular body configured to transport pressurized treatment air between a proximal end of the tubular body and a distal end of the tubular body, the proximal end being configured to connect to a patient interface, and the distal end being configured for connection to an air delivery tube; and a sensor being configured to generate a signal based on air passing at the proximal end for diagnosis and / or treatment of a respiratory disorder.

A patient support apparatus for inferring a patient's future behavior tracks data related to patient bed exits from the patient support apparatus. A controller may be in communication with the patient support apparatus. The controller may include a processor and a non-transitory memory device. The memory device may include instructions that, when executed by the processor, acquire data related to patient bed exits.

An improved analyte monitoring system having a sensor and a transceiver with improved communication and / or user interface capabilities. The transceiver may communicate with and power the sensor. The transceiver may receive one or more analyte measurements from the sensor and may calculate one or more analyte concentrations based on the received analyte measurements. The transceiver may generate analyte concentration trends, alerts, and / or alarms based on the calculated analyte concentrations. The system may also include a display device, which may be, for example, a smartphone and may be used to display analyte measurements received from the transceiver. The display device may execute a mobile medical application. The system may include a data management system, which may be web-based.

The disclosure relates to a method of determining a desired rest period for a phosphagen regime physical activity of a user, comprising determining an end of the physical activity and the start of a rest period of the user and measuring an oxygen consumption during the rest period. The method comprises determining whether said oxygen consumption meets one or more predetermined parameter; and providing an indication if the one or more parameter is met.

According to an aspect, there is provided a computer-implemented method (200) of determining a concentration of glucose in blood of a subject, the method comprising: acquiring (202) first measurement data indicative of a response resulting from an interaction of an electromagnetic (EM) signal with blood of the subject in a body part of the subject; acquiring (204) second measurement data indicative of at least one parameter associated with the subject; and inferring (206) a concentration of glucose in the blood of the subject from the first measurement data and the second measurement data using a predictive model, the predictive model having been trained to infer a concentration of glucose in the blood of the subject from the first measurement data and the second measurement data.

The invention relates to the technical field of medical equipment, and discloses a medical image acquisition device which comprises a device base and a man-machine interaction device, a bed board is fixedly connected to the top of the device base, a positioning groove is formed in the top of the bed board, a grip and a positioning block are arranged on the side face of the positioning groove, and the grip and the positioning block are fixedly connected with the bed board; a fixing device is fixedly connected to the side face of the bed board, a scanning device is fixedly connected to the top of the fixing device, and a data acquisition module, a data preprocessing module, a data processing module, a data analysis module and a data transmission module are arranged in the scanning device; the device is provided with the data acquisition module and the data preprocessing module, respiration and motion frequencies of a to-be-detected person can be acquired, reduction of the number of motion artifacts and the probability of occurrence of the motion artifacts is facilitated, and therefore the acquisition efficiency and accuracy are improved; and the working intensity of medical staff can be reduced, so that the image acquisition efficiency is improved.

The application discloses a fall detection method and system based on a wrist inertia sensor, and the method comprises the following steps: acquiring motion data collected by an inertia sensor installed on a human wrist and performing pretreatment to obtain target motion data; constructing a fall detection model and a fall direction detection model based on one-dimensional convolution and a long short-term memory neural network; performing fall detection by using the fall detection model; if falls are detected for a continuous setting number of times, it is confirmed that a fall occurs, then fall direction detection is performed by using the fall direction detection model, and a fall direction detection result is output. The application combines the advantages of a convolution neural network and a long short-term memory neural network to construct the fall detection model and the fall direction detection model, not only realizes automatic recognition of a fall direction, but also improves the accuracy of fall detection; and a judgment method based on multiple continuous sliding window data can effectively avoid that an approximate fall behavior is wrongly judged as a fall.

A system for treating at least one of the conditions depression and atrial fibrillation, the system comprising: a) a bracket configured to be attachable to a tragus of the subject, the bracket comprising: i) opposing arms configured such that a distal end of the arms is biased towards each other; and ii) electrodes positioned near a distal end of the arms on opposite surfaces so that the electrodes are pressed into engagement with opposite surfaces of the tragus; and b) a signal generator electrically connected to the electrodes, the signal generator being configured to generate at least one therapy signal that can be applied to the vagus nerve within the tragus via the electrodes to thereby modulate the vagus nerve and treat depression and / or atrial fibrillation.

Systems and methods for identifying physiological states of human subjects are disclosed herein. In one embodiment, a system receives, from one or more sensors, physiological signals of a human subject. The system processes the physiological signals to extract feature signals as time series. The system identifies change points in the feature signals. The system identifies critical change points in the feature signals by applying a voting process to the change points in the feature signals. The system partitions the feature signals into segments based on the critical change points. The system detects a predetermined physiological state (an anomalous physiological state) of the human subject by applying clustering and probabilistic analysis to the segments. In response to detecting the predetermined physiological state, the system automatically takes an action to assist the human subject.

The present application relates to the field of human posture detection, and particularly relates to a human target posture detection method and system and a control method of intelligent products, which comprises the following steps: a first sensing component is used to emit a first detection signal, a two-dimensional receiving sensing component is used to receive the signal reflected by a human target, and a signal processor is used to process the signal received by the two-dimensional receiving sensing component to obtain contour information of the human target; a second sensing component is used to emit a second detection signal, the two-dimensional receiving sensing component is used to receive the signal reflected by the human target, and the signal processor is used to process the signal received by the two-dimensional receiving sensing component to obtain heart distance information and determine the position of the heart in the contour information according to the heart distance information; and the signal processor is used to determine the posture of the human target according to the relative position relationship between the position of the heart and the contour information. The present application can realize a variety of combined non-inductive human posture recognition, control the work of related intelligent products according to the detected posture, and realize non-inductive interaction.

Provided is a respiratory rate measurement device provided with: a patient connection unit for acquiring biological information for detecting respiration from a user; a conversion unit for converting the biological information detected by the patient connection unit into an electric signal; a respiratory rate calculation unit for processing the converted electrical signal and calculating a respiratory rate; and a signal output unit that outputs the calculated respiratory rate by means of at least one of voice, screen display, and communication signals. And a respiratory rate calculation unit that calculates respiratory accompanying information including a respiratory interval for each respiration detected on the basis of the electrical signal or an amplitude of a detected respiratory waveform, calculates an index relating to reliability of the calculated respiratory rate on the basis of the respiratory accompanying information, and outputs the index by means of the signal output unit. The respiratory rate measuring device is configured to calculate the respiratory rate and calculate an index related to the stability of the respiration, thereby determining the condition in which the respiration can be stably detected.

Provided are systems, methods, and devices for providing mediation of a traumatic brain injury. Systems may include an interface, processing devices, and a controller. The interface is configured to obtain measurements from a brain of a user with a traumatic brain injury. A first processing device is configured to generate multiple brain state parameters characterizing one or more features of a brain state of the user. A second processing device is configured to generate models of the brain of the user based on the plurality of brain state parameters and the plurality of measurements, and determine, using the models and training data comprising one or more mediation data points, a mediation procedure for reducing one or more symptoms of the traumatic brain injury. The mediation procedure is provided to one or more entities, and one or more control signals are generated by the controller based on the mediation procedure.

An embodiment of the present invention provides a method for providing a signal loss notification in a blood glucose measurement system, comprising: a step in which a terminal delays a signal loss notification for a first period when a communication failure occurs between the terminal and a sensor transmitter; a step in which the terminal further determines whether a signal loss continues during a second period when the communication failure continues during the first period; a step in which the terminal generates the signal loss notification when the signal loss continues during the second period; and a step in which the terminal outputs the signal loss notification to a user.

The present invention relates to a system comprising a first non-contact sensor configured to generate first sensor data, and one or more processors configured to receive the first sensor data, isolate, using a classification system, periods of the first sensor data in which respiratory-related movement is predominant from periods of the first sensor data in which bodily movement is predominant based on a frequency value derived from the first sensor data, obtain, using the classification system, respiratory data from the periods of the first sensor data in which respiratory-related movement is predominant, obtain, using the classification system, objective data from the respiratory data and the periods of the first sensor data in which bodily movement is predominant, calculate a quality of life index based on the objective data, and generate feedback based on the calculated quality of life index.

The invention comprises a device and method to estimate the elasticity of soft elastic solids from surface wave measurements. The method is non-destructive, reliable and repeatable. The final device is low-cost and portable. It is based in audio-frequency shear wave propagation in elastic soft solids. Within this frequency range, shear wavelength is centimeter sized. Thus, the experimental data is usually collected in the near-field of the source. Therefore, an inversion algorithm taking into account near-field effects was developed for use with the device. Example applications are shown in beef samples, tissue mimicking materials and in vivo skeletal muscle of healthy volunteers

The present invention refers to a respiratory therapy device comprising: a mouthpiece defining a longitudinal axis and having an end port; a housing connected to the mouthpiece and having a top surface, wherein at least a portion of the top surface is longitudinally spaced from the end port and defines a viewing surface adapted to be visible to a user having the end port disposed in a mouth of the user; and a feedback array disposed on the viewing surface, wherein the feedback array extends diagonally across the viewing surface and is curved or curvi-linear.

The present invention relates to a patient monitor (20) ) configured to simultaneously obtain a plurality of measurement signals from a subject (10) and to display one or more of the measurements signals and / or one or more parameters derived therefrom, the patient monitor (20) comprising two or more universal ports (21) each configured to connect a cable (12) having a universal connector (13) fitting into a universal port (21) for providing a measurement signal from a subject (10) to the patient monitor (20), a detection unit (28) configmed to detect a type of cable connected to the universal port (21), the type of cable relating to a type of measurement; and an optical indicator (22) per universal port (21), configured to indicate the type of cable connected to the respective universal port (21) wherein the two or more optical indicators (22) are arranged at, around and / or next to the respective universal port (21) and are configured to indicate the type of cable connected to the respective universal port (21).