7 results about "Physiological values" patented technology

Disclosed herein is a method for diagnosing a medical condition in a patient. The method comprises: obtaining, from the patient, a plurality of physiological values; implementing a first model configured to determine risk values for at least one of a plurality of medical conditions, based on the physiological values. Implementing the first model comprises: obtaining a first risk value for the at least one medical condition, based on a first one of the obtained physiological values; and weighting the first risk value based on a second one of the obtained physiological values, to determine a total risk value of the at least one medical condition for the patient.

Embodiments include systems and methods for determining a physiological value of a user. The systems and methods described herein may be configured to select and obtain physiological metrics from multiple electronic devices in order to generate an output physiological value for a measured physiological parameter. In some cases, an electronic device is configured to receive physiological metrics from one or more other electronic devices and generate the output physiological value using one or more of the received physiological metrics. Additionally, in some cases, the electronic device may be configured to generate a physiological metric (e.g., using a physiological sensor incorporated in the electronic device), and may use both the generated physiological metric and the one or more received physiological metrics in generating the output physiological value.

The present application relates to the technical field of health monitoring, and discloses a home health risk assessment method and system based on night sleep activity. The present application collects night sleep physiological data and night activity trajectory data of a user through a sign monitoring module under a mattress and a night behavior trajectory module in a residence, and uploads the data after time stamp alignment by a gateway. Abnormal physiological values are cleaned out, sleep-behavior correlation features are constructed, and composite features such as difficulty falling asleep, heart rate sudden change and apnea are extracted. The risk of heart, respiration and cognitive decline is assessed in different dimensions, and long-term risk aggravation warning can be generated through 30-day personal dynamic baseline and linear regression significance analysis. The present application solves the problems of data isolation, rough index and cognitive assessment blind area in the prior art, realizes non-invasive and accurate early warning of home health, and is suitable for home care monitoring of the elderly.

The invention discloses a medical report interpretation method and device based on multi-modal dynamic knowledge fusion, and the method comprises the steps: recognizing a key region of a target medical report, and extracting a target physiological value index and a target text description index; inputting the baseline feature data into a physiological index interval prediction model to obtain a physiological index reference interval; calculating the physiological value index deviation degree according to the target physiological value index and the physiological index reference interval, and determining the abnormal degree of the physiological value index; key descriptors are extracted, and disease entities, standard text description and disease severity are inquired in the multi-dimensional medical knowledge graph; calculating the semantic similarity between the target text description index and the standard text description, and determining the abnormal degree of the text description index in combination with the disease severity; and determining a comprehensive anomaly score according to the physiological value index anomaly degree and the text description index anomaly degree. The method improves the accuracy and comprehensiveness of medical report interpretation, and can be widely applied to the technical field of artificial intelligence.

This invention relates to an intelligent exoskeleton system integrating environmental perception and physiological indicator monitoring, belonging to the field of intelligent exoskeleton protection. The solution first synchronizes multi-source sensor data in the time domain, and then inverts the theoretically expected physiological values ​​corresponding to the current work intensity based on joint movement speed and interaction torque. By calculating the physiological condition residual between the measured physiological data and the theoretical expected values, the system can dynamically isolate physiological indicator fluctuations caused by the movement itself, thereby extracting the true risk characteristics caused only by environmental risks or physical abnormalities. Based on this, it combines environmental parameters to perform correlation risk discrimination, accurately identifying specific risk types such as environmental risks or abnormal physiological indicators. Finally, the system automatically matches differentiated target impedance parameters and tactile cue signals according to the identification results, achieving active safety control and precise risk warning of the exoskeleton without interfering with high-intensity normal work.

The invention discloses a multi-mode invasive pressure sensor based on embedded artificial intelligence induction, and relates to the technical field of medical instruments, the multi-mode invasive pressure sensor comprises a sensor shell, a multi-mode sensing array and a fluid channel communicated with the multi-mode sensing array are integrated in the sensor shell, and a micro pump is arranged at the inlet end of the fluid channel; the system further comprises an embedded manual processing system. By providing an integrated architecture of a multi-modal sensing array and embedded AI processing, an embedded AI algorithm recognizes and corrects waveform distortion caused by over-damping and under-damping in real time, it is ensured that reading of systolic pressure and diastolic pressure accurately reflects real physiological values, the pressure measurement error is reduced, the precision is improved, and the measurement accuracy is improved. According to the present invention, the clinical high precision requirement on the vasoactive drug titration is met, the automatic diagnosis can be performed, the optimal dynamic response state can be rapidly adjusted, the sensor is particularly suitable for the time-sensitive emergency and operation environment, the sensor has the high overall waterproof grade, the clinical routine disinfection can be tolerated, and the service life meets the disposable use requirement.

The physiological value sensing device comprises a sensing module, a calibration module, and a signal processing module. The sensing module includes a sensing emission unit and a sensing receiving unit. The sensing emission unit emits a sensing light to a target tissue. The sensing light is reflected by the target tissue to the sensing receiving unit, generating a sensing signal. The calibration module includes a calibration emission unit and a calibration receiving unit. The calibration emission unit emits a calibration light to the calibration receiving unit to produce a reference signal. The signal processing module includes a denoising unit and a signal conversion unit. The denoising unit adjusts the sensing signal using the reference signal. The signal conversion unit extracts at least one peak value to form an extracted signal, selects a weight corresponding from a physiological value model, and narrows a bandwidth of the extracted signal to produce a physiological value signal.