11 results about "Thoracic Fluid" patented technology

The application discloses a thoracic cavity closed drainage bottle, which comprises a collecting bottle, a water seal bottle and a pressure measuring bottle, a liquid level alarm assembly and a fan assembly are arranged in the collecting bottle, a connecting pipe is arranged at the top end of the collecting bottle, and a dredging assembly is arranged in the connecting pipe; the liquid level alarm assembly is hung in the collecting bottle; the fan assembly is arranged below the bottom end of the connecting pipe which extends into the collecting bottle; the dredging assembly comprises a pressure increasing part, first opening and closing valves, second opening and closing valves, third opening and closing valves and a side pipe; the first opening and closing valves and the second opening and closing valves are arranged at the top end and the bottom end of the connecting pipe; the pressure increasing part is arranged outside the top end of the connecting pipe, and the side pipe is arranged outside the bottom end of the connecting pipe; and the third opening and closing valves are arranged in the side pipe. The application can monitor the amount of thoracic fluid in the collecting bottle, can determine the tendency of active bleeding in time, can give a prewarning when the amount of thoracic fluid in the collecting bottle is about to be full, and can automatically dredge when the pipeline is blocked during the drainage process, so that the tube pulling operation is not needed, and the pain of the patient is reduced.

A mobile bodily imaging system for determination of a lung fluid content is provided, comprising: a stepped-frequency radar generator that generates one or more tone and transmits the one or more tone into a chest of the patient; a sparse deconvolution inversion algorithm to detect reflection points indicating tissue interfaces within the patient and create a sparsity-based image; an initial model generated using Markov Chain Monte Carlo or Deep Neural Network estimates; and a final model generated using a neural renderer, wherein the neural renderer is provided with confirmed data that permits the neural renderer to predict the form of the reflection points, wherein the neural renderer creates an image that is compared to the sparsitybased image, and wherein the neural renderer creates refined images in a number of iterations and / or based upon a predetermined threshold of a difference between the refined neural renderer image and the sparsity-based image.

Systems and methods are providing for detecting and monitoring thoracic fluid, air-trapping and ventilation assessment in real time, wherein data obtained from a non-invasive electrode patch is analyzed using analysis algorithms for an electrical equivalent model that have been personalized for a patient's physiologic characteristics, medical condition and / or historical medical information using machine learning trained on a dataset representative of a large and diverse patient population. The systems and methods provide a simple, real-time, highly sensitive and specific, non-invasive, bedside solution for fluid level assessment, checking for increased air trapping, and ventilation assessment. The described methods include a variety of use cases for the inventive system and methods.

Systems and methods are providing for detecting and monitoring thoracic fluid, air-trapping and ventilation assessment in real time, wherein data obtained from a non-invasive electrode patch is analyzed using analysis algorithms for an electrical equivalent model that have been personalized for a patient's physiologic characteristics, medical condition and / or historical medical information using machine learning trained on a dataset representative of a large and diverse patient population. The systems and methods provide a simple, real-time, highly sensitive and specific, non-invasive, bedside solution for fluid level assessment, checking for increased air trapping, and ventilation assessment. The described methods include a variety of use cases for the inventive system and methods.

Systems and methods are providing for detecting and monitoring thoracic fluid, air-trapping and ventilation assessment in real time, wherein data obtained from a non-invasive electrode patch is analyzed using analysis algorithms for an electrical equivalent model that have been personalized for a patient's physiologic characteristics, medical condition and / or historical medical information using machine learning trained on a dataset representative of a large and diverse patient population. The systems and methods provide a simple, real-time, highly sensitive and specific, non-invasive, bedside solution for fluid level assessment, checking for increased air trapping, and ventilation assessment. The described methods include a variety of use cases for the inventive system and methods.

The utility model relates to the field of medical instruments, and discloses an improved chest bottle which comprises a chest bottle body, a drainage mechanism is fixedly connected to one side of the upper end of the chest bottle body, and a storage mechanism is arranged on one side in the chest bottle body in a threaded mode. According to the utility model, the drainage mechanism is provided with the water injection hard valve, the water injection pipe and the balloon, and the water injection hard valve on one side of the water injection pipe is used for injecting water into the balloon, so that the balloon is expanded and is tightly attached to tissues in the thoracic cavity of a patient, and the drainage pipe is firmly fixed at a specific position in the thoracic cavity; the lower shell and the bottle body are connected in a clamping mode, the clamping structure can ensure that the lower shell and the bottle body are stably connected, disassembly is simple, the collecting bottle is connected with the chest bottle body through the connecting column, and the collecting bottle is convenient to use. And chest fluid can be collected in the collecting bottle.

A mobile bodily imaging system for determination of a lung fluid content is provided, comprising: a stepped-frequency radar generator that generates one or more tone and transmits the one or more tone into a chest of the patient; a sparse deconvolution inversion algorithm to detect reflection points indicating tissue interfaces within the patient and create a sparsity-based image; an initial model generated using Markov Chain Monte Carlo or Deep Neural Network estimates; and a final model generated using a neural renderer, wherein the neural renderer is provided with confirmed data that permits the neural renderer to predict the form of the reflection points, wherein the neural renderer creates an image that is compared to the sparsity based image, and wherein the neural renderer creates refined images in a number of iterations and / or based upon a predetermined threshold of a difference between the refined neural renderer image and the sparsity-based image.

Systems and methods are providing for detecting and monitoring thoracic fluid, air-trapping and ventilation assessment in real time, wherein data obtained from a non-invasive electrode patch is analyzed using analysis algorithms for an electrical equivalent model that have been personalized for a patient's physiologic characteristics, medical condition and / or historical medical information using machine learning trained on a dataset representative of a large and diverse patient population. The systems and methods provide a simple, real-time, highly sensitive and specific, non-invasive, bedside solution for fluid level assessment, checking for increased air trapping, and ventilation assessment. The described methods include a variety of use cases for the inventive system and methods.

Systems and methods are providing for detecting and monitoring thoracic fluid, air-trapping and ventilation assessment in real time, wherein data obtained from a non-invasive electrode patch is analyzed using analysis algorithms for an electrical equivalent model that have been personalized for a patient's physiologic characteristics, medical condition and / or historical medical information using machine learning trained on a dataset representative of a large and diverse patient population. The systems and methods provide a simple, real-time, highly sensitive and specific, non-invasive, bedside solution for fluid level assessment, checking for increased air trapping, and ventilation assessment. The described methods include a variety of use cases for the inventive system and methods.

This invention relates to the field of medical device technology, specifically providing a pleural drainage device with monitoring function. This device, through the coordinated design of a first buoyancy component, a second buoyancy component, and a laser beam warning component, can accurately monitor the amount of fluid accumulated in the drainage cavity. When the fluid accumulation in the drainage cavity reaches the warning threshold, a counterweight pushes a horizontal plate downwards, causing a baffle to block the laser detection light path, triggering an audible and visual alarm. This promptly reminds medical staff to replace the drainage device, solving the problems of traditional drainage bottles lacking full-bottle warnings and being prone to pleural fluid overflow or backflow, thus ensuring the safety of the drainage operation.

The present application belongs to the technical field of medical devices, and particularly relates to a thoracic surgery nursing thoracic duct fixing support, which comprises a supporting rod, a sleeve and a detection assembly are fixedly connected to the middle part of the supporting rod, an adjusting assembly, the inner cavity of the supporting rod is provided with a lifting assembly, the top of the lifting assembly is provided with a rotating assembly, a fixing assembly, the fixing assembly comprises a bending assembly arranged at the top of the rotating assembly, the inside of the bending assembly is slidably connected with a positioning assembly, and the bottom of the positioning assembly is provided with a clamping assembly. The present application can adjust the height and orientation of the device according to requirements, can also adjust the position of the pipeline fixation, the orientation of the pipeline fixation, and the path of the positioning, can randomly control the movement or fixation of the device, and can detect the thoracic fluid discharge in time and monitor the patient's physical condition in real time during the use of the thoracic duct, so as to improve the safety.