8 results about "Subjective data" 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.

A technology system implements processing apparatus, such as one or more server(s) and / or respiratory therapy device(s) (4000), to characterize insomnia such as for comorbid sleep apnea and insomnia (COMISA) subjects. The technology may be implemented with artificial intelligence, such as machine learning. The technology may be configured to receive objective data relating to a user's therapy and / or sleep from sensor(s) associated with the user. The sensor(s) may be in. or associated with, a positive airway pressure (PAP) device. The technology may be configured to receive subjective data relating to the user's sleep. The technology may be configured to input the objective data and subjective data into a classification system or classifier. The classifier may then apply the objective and subjective data to (a) determine key characteristics for patients that distinguish phenotypes of COMISA; and / or (b) distinguish phenotypes of COMISA based on previously7 determined ones of the key characteristics.

The application belongs to the technical field of aviation safety and biomedical engineering, and discloses a navigation maintenance personnel fatigue risk estimation system and method, which comprises collecting objective data, subjective data and multi-life sign data; extracting and fusing subjective and objective fatigue cause factors, and outputting fatigue risk assessment results; pre-processing the multi-life sign data and extracting time-frequency characteristics; performing correlation analysis and difference analysis on the time-frequency characteristics of the multi-life sign data, establishing a fatigue state recognition model based on the multi-life sign data, and outputting fatigue cause factors corresponding to each physiological channel; using a subjective and objective weighting method to weight and fuse the fatigue risk assessment results and the fatigue cause factors, and outputting real-time fatigue risk prediction results; the application also provides a system for realizing the above method; through subjective and objective data fusion, multi-physiological channel recognition and dynamic weight distribution of multi-cause factors, real-time estimation of the fatigue risk of navigation maintenance personnel is realized.

This invention discloses an intelligent electro-pulse therapy control method based on AI adaptive feedback, relating to the field of electro-pulse therapy control. The method includes the following steps: collecting biofeedback signals from the therapy user and simultaneously collecting the user's subjective feedback data; converting the subjective feedback data into effective subjective data and performing preliminary analysis of the feedback analysis data between different biofeedback signals and subjective feedback data; deeply analyzing the influence of different biofeedback signals on the subjective feedback data, and simultaneously constructing historical reference analysis schemes and predictive reference analysis schemes to calibrate the impact on the feedback analysis data, obtaining feedback reference data; and intelligently controlling the intelligent electro-pulse therapy based on the feedback reference data. This invention addresses the problem that existing electro-pulse therapy control technologies lack intelligent and accurate acquisition of pain perception, resulting in an inability to adjust the intensity of the electro-pulse in a timely and accurate manner.

This application provides a diagnostic scheme recommendation method, electronic device, and medium. The method includes: acquiring patient sequence data; determining a first historical diagnostic scheme matching the patient based on a first preset knowledge base; correcting the first historical diagnostic scheme based on a first difference between the first medication data and the second medication data in the matched first historical diagnostic scheme, a second difference between the first indicator data and the second indicator data in the matched first historical diagnostic scheme, a first difference between the first diagnostic result and the second diagnostic result in the matched first historical diagnostic scheme, and a second difference between the first subjective data and the second subjective data in the matched first historical diagnostic scheme; inputting the corrected first historical diagnostic scheme into a clinical efficacy verification model and outputting a predictive indicator; and determining whether the predictive indicator meets a preset standard based on the first diagnostic result and the second preset knowledge base.

The invention provides a post-anesthesia patient state evaluation method and system, and belongs to the technical field of data analysis, and the method comprises the steps: obtaining first subjective data and first objective data of a patient before an operation, and obtaining second subjective data and second objective data of the patient at different time periods after the operation; fusing the first subjective data and the first objective data to obtain a first comprehensive score; fusing the second subjective data of each time period and the second objective data of each time period to obtain a plurality of second comprehensive scores; and based on the time sequence, respectively calculating deviations between the plurality of second comprehensive scores and the first comprehensive score, and based on the change rate of the deviations, evaluating the state of the patient after anesthesia. According to the post-anesthesia patient state evaluation method and system provided by the invention, the accuracy of post-anesthesia patient state evaluation can be improved.

The application discloses a kind of based on children allergic rhinitis desensitization treatment tracking system, it is related to children allergic rhinitis desensitization treatment technical field, including: data acquisition module, for synchronously obtaining physiological signal data and discrete symptom evaluation data of target child in initial period of desensitization treatment;Signal processing module is used for the frequency domain analysis to physiological signal data, and the day rate heart rate variability index reflecting sympathetic and parasympathetic nervous balance degree of autonomous nervous system is calculated.This application establishes the dynamic calibration mechanism of objective physiological index to subjective symptom data, effectively eliminates the subjective perception deviation when physiological state is abnormal, so that symptom score can accurately reflect the real rhinitis inflammation load of child, effectively solve the traditional subjective and objective data static split, subjective data low reliability Problem, corrects data distortion problem, can reliably reflect real pathophysiological change, improve the accuracy of subsequent judgment result.

The invention discloses a method for estimating the failure probability of chemical equipment and parts by fusing subjective data and objective data and a related device. The estimation method comprises the following steps: acquiring objective data and subjective data of a fault interval; performing fusion estimation on the objective data and the subjective data of the fault interval by adopting a Bayesian theory to obtain maximum posterior distribution of fault interval distribution parameters; and calculating the equipment fault probability according to the maximum posterior distribution of the fault interval distribution parameters. Based on the Bayesian theory, the fault interval objective data and subjective data are subjected to fusion estimation, the maximum posterior distribution of fault interval distribution parameters is obtained, and the problems that objective sample data for failure intervals are insufficient and expert experience failure data are not fully utilized are solved. According to the method, the objective data and the subjective data of the fault interval are fused, so that the existing information can be utilized to the maximum extent, and the problem of unstable estimation result or overlarge deviation caused by insufficient objective data is avoided.