5 results about "Subjective data" patented technology

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 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.