14238results about "Catheter" patented technology

In one embodiment, a medical system includes a catheter configured to be inserted into a chamber of a heart of a living subject, and including multiple electrodes configured to capture electrical activity from electrical activation signals propagating in tissue of the chamber, a display, and processing circuitry configured to automatically select bipolar signals to be captured into an electro-anatomical map from respective electrode pairs of the multiple electrodes responsively to an alignment of the respective electrode pairs with a direction of propagation of the electrical activation signals, and render the electro-anatomical map to the display.

NADP-dependent oxidoreductase compositions, and electrodes, sensors and systems that include the same. Analyte sensors include an electrode having a sensing layer disposed thereon, the sensing layer comprising a polymer and an enzyme composition distributed therein. The enzyme composition includes nicotinamide adenine dinucleotide phosphate (NAD(P)+) or derivative thereof, an NAD(P)+-dependent dehydrogenase; an NAD(P)H oxidoreductase; and an electron transfer agent comprising a transition metal complex.

NADP-dependent oxidoreductase compositions, and electrodes, sensors and systems that include the same. Analyte sensors include an electrode having a sensing layer disposed thereon, the sensing layer comprising a polymer and an enzyme composition distributed therein. The enzyme composition includes nicotinamide adenine dinucleotide phosphate (NAD(P)+) or derivative thereof, an NAD(P)+-dependent dehydrogenase; an NAD(P)H oxidoreductase; and an electron transfer agent comprising a transition metal complex.

The present disclosure provides a method and system for analyzing unipolar electrophysiological (EP) signals acquired by a multi-electrode catheter placed in a ventricle of a patient's heart. The method includes receiving unipolar EP signals, extracting unipolar far-field signals from the unipolar EP signals, and analyzing the extracted unipolar far-field signals to estimate the distribution of scar regions across a thickness of wall tissue of the ventricle. Using the estimated distribution, a unipolar far-field EP map showing the scar regions is generated. The method further includes displaying the unipolar far-field EP map including the scar regions to a user. The system comprises a display device and a processor configured to perform the steps of the method.

Glucose and ketones may be dysregulated singularly or concurrently in certain physiological conditions and may be advantageously assayed together using an analyte sensor capable of detecting both analytes. Certain analyte sensors capable of dual detection may comprise a first working electrode and a second working electrode, a ketones-responsive active area disposed upon a surface of the first working electrode, a glucose-responsive active area comprising a glucose-responsive enzyme disposed upon a surface of the second working electrode, a membrane having a first portion overcoating the ketones-responsive active area and a second portion overcoating the glucose-responsive active area, in which the first portion and the second portion have different compositions. The ketones-responsive active area comprises an enzyme system comprising at least two enzymes that are capable of acting in concert to facilitate detection of ketones.

Methods and analyte sensors including at least a first working electrode having a first active area thereon, and performing a dip coating operation to deposit a bilayer membrane upon the first working electrode and the first active area. The bilayer may include an inner layer having a first membrane polymer and an outer layer having a second membrane polymer, the first membrane polymer and the second membrane polymer differing from one another. The dip coating operation may comprise one or more first dips in a first membrane formulation to form the inner layer of the bilayer membrane and one or more second dips in a second membrane formulation to form the outer layer of the bilayer membrane upon the inner layer.

Methods and analyte sensors including at least a first working electrode having a first active area thereon, and performing a dip coating operation to deposit a bilayer membrane upon the first working electrode and the first active area. The bilayer may include an inner layer having a first membrane polymer and an outer layer having a second membrane polymer, the first membrane polymer and the second membrane polymer differing from one another. The dip coating operation may comprise one or more first dips in a first membrane formulation to form the inner layer of the bilayer membrane and one or more second dips in a second membrane formulation to form the outer layer of the bilayer membrane upon the inner layer.

NADP-dependent oxidoreductase compositions, and electrodes, sensors and systems that include the same. Analyte sensors include an electrode having a sensing layer disposed thereon, the sensing layer comprising a polymer and an enzyme composition distributed therein. The enzyme composition includes nicotinamide adenine dinucleotide phosphate (NAD(P)+) or derivative thereof; an NAD(P)+-dependent dehydrogenase; an NAD(P)H oxidoreductase; and an electron transfer agent comprising a transition metal complex.

NADP-dependent oxidoreductase compositions, and electrodes, sensors and systems that include the same. Analyte sensors include an electrode having a sensing layer disposed thereon, the sensing layer comprising a polymer and an enzyme composition distributed therein. The enzyme composition includes nicotinamide adenine dinucleotide phosphate (NAD(P)+) or derivative thereof; an NAD(P)+-dependent dehydrogenase; an NAD(P)H oxidoreductase; and an electron transfer agent comprising a transition metal complex.

The invention relates to the technical field of blood pressure measurement, in particular to a cuff-free blood pressure continuous monitoring method based on ICG, PPG and ECG multi-mode physiological signals. According to the method, deep mining and fusion are carried out based on multi-modal physiological signals such as a chest impedance signal ICG, a photoelectric volume pulse wave signal PPG and an electrocardiosignal ECG of a tested object synchronously collected by multi-modal hemodynamics monitoring equipment, and a richer multi-modal feature matrix related to blood pressure changes is constructed; after deep learning fusion training is carried out on the constructed cuff-free blood pressure prediction model, prediction output of a cuff-free blood pressure prediction result can be directly carried out according to ICG, PPG and ECG multi-mode physiological signals of a to-be-detected tested object by means of the cuff-free blood pressure prediction model, the generalization ability and monitoring precision of continuous monitoring of the cuff-free blood pressure can be effectively improved, and the accuracy of continuous monitoring of the cuff-free blood pressure can be improved. The continuous, non-invasive and high-precision blood pressure monitoring requirements are met, and the clinical application value is more remarkable.

NADP-dependent oxidoreductase compositions, and electrodes, sensors and systems that include the same. Analyte sensors include an electrode having a sensing layer disposed thereon, the sensing layer comprising a polymer and an enzyme composition distributed therein. The enzyme composition includes nicotinamide adenine dinucleotide phosphate (NAD(P)+) or derivative thereof, an NAD(P)+-dependent dehydrogenase; an NAD(P)H oxidoreductase; and an electron transfer agent comprising a transition metal complex.

NADP-dependent oxidoreductase compositions, and electrodes, sensors and systems that include the same. Analyte sensors include an electrode having a sensing layer disposed thereon, the sensing layer comprising a polymer and an enzyme composition distributed therein. The enzyme composition includes nicotinamide adenine dinucleotide phosphate (NAD(P)+) or derivative thereof; an NAD(P)+-dependent dehydrogenase; an NAD(P)H oxidoreductase; and an electron transfer agent comprising a transition metal complex.

The invention relates to a sensor head device for a heart support system, wherein the sensor head device has at least one sensor carrying element, wherein the sensor carrying element has at least one sensor cavity for accommodating at least one sensor and / or at least one signal transmitter cavity for accommodating at least one signal transmitter.

In an embodiment, a cryoablation probe includes a shaft, where the shaft has a supply tube, a return tube surrounding the supply tube, an insulated portion, wherein a vacuum circuit runs through the insulated portion between the return tube and an insulating shaft, and an expansion chamber extending distally to the insulated portion. The probe further includes a distal tip configured to seal a distal end of the return tube. The distal tip has a tip portion extending distally from the distal end of the return tube and a plug portion configured to be inserted inside of the return tube. The probe includes a compressive element surrounding the return tube and the plug portion of the distal tip, configured to seal the distal tip to the return tube.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

This disclosure generally relates to medical devices that include a sensor transmitter assembly that includes a sensor assembly including a sensor module where a first sensor including a first sensor head having at least one first sensor contact pad is combined with a second sensor including a second sensor head having at least one second sensor contact pad. The sensor transmitter assembly also includes a transmitter assembly positioned on a top of the sensor assembly to form a single unit, the transmitter assembly having at least one transmitter contact disposed on a base of the transmitter assembly, where the first sensor contact pad(s) and the second sensor form a connection path with the transmitter contact(s).

Methods and analyte sensors including at least a first working electrode having a first active area thereon, and performing a dip coating operation to deposit a bilayer membrane upon the first working electrode and the first active area. The bilayer may include an inner layer having a first membrane polymer and an outer layer having a second membrane polymer, the first membrane polymer and the second membrane polymer differing from one another. The dip coating operation may comprise one or more first dips in a first membrane formulation to form the inner layer of the bilayer membrane and one or more second dips in a second membrane formulation to form the outer layer of the bilayer membrane upon the inner layer.

The present disclosure involves a medical device. The medical device includes an elongate cable assembly having a distal connector, a proximal connector, and a cable body coupling the proximal and distal connectors. The distal connector is configured for coupling with a diagnostic medical device. The proximal connector is configured for coupling with a medical measurement system. An electronic component is located inside the distal connector or the associated cable housing. The electronic component includes an analog-to-digital converter (ADC) and a microprocessor. The ADC is configured to receive medical data gathered by the diagnostic medical device and convert the medical data into digital signals. The microprocessor is coupled to an output of the ADC and configured to process the digital signals into a format that is readable by the medical measurement system.

A neurosurgery system for probing brain tissue of a patient for tumorous tissue. The system including a suction tool, an excitation source, an optical instrument, and a controller. The suction tool including a suction cannula defining a lumen, an optical fiber configured to transmit fluorescence emitted by the brain tissue; and an indicator configured to selectively emit visible light. An excitation source is configured to emit an excitation light having a wavelength to induce the fluorescence in the tumorous tissue. The optical instrument is coupled to the optical fiber. The optical instrument configured to convert the fluorescence emitted by the brain tissue and transmitted by the optical and configured to determine that the brain tissue is tumorous based on the electrical signal and activate the indicator based on the determination.

The invention discloses a method and system for reducing data errors of a dynamic glucometer, and the method comprises the steps: collecting a current signal of fluid between subcutaneous tissues in real time through an implantable sensor, and synchronously recording the working environment parameters of the sensor; carrying out denoising and normalization processing on the current signal, and carrying out temperature compensation and drift correction on the signal according to a working environment parameter; extracting time sequence features and frequency domain features from the signals processed in the step S2; training a machine learning model based on the time sequence feature data and the frequency domain feature data, wherein the machine learning model is used for predicting the blood glucose concentration and identifying abnormal data points; correcting a model prediction result through residual analysis and weighted adjustment, and performing secondary correction on abnormal data points in combination with event data input by a patient; and outputting the optimized blood glucose data to a terminal display device in a time sequence curve form. Through the process, the influence of abnormal state data on blood glucose monitoring is reduced, and the data stability is improved.

The invention is suitable for the technical field of intelligent wearable devices, and provides a blood pressure dynamic calibration method and device of an intelligent wearable device and the wearable device. According to the blood pressure dynamic calibration method of the intelligent wearable device, the dual-wavelength pulse wave signal collected by the dual-wavelength PPG sensor is obtained, differential processing is conducted on the dual-wavelength pulse wave signal, the purified pulse wave signal is obtained, the signal-to-noise ratio of the purified pulse wave signal is calculated, and when the signal-to-noise ratio is higher than the threshold value, the blood pressure dynamic calibration of the intelligent wearable device is completed. Extracting a pulse wave characteristic value from the purified pulse wave signal, iterating the vascular elasticity coefficient according to the pulse wave characteristic value to obtain an iterative vascular elasticity coefficient, and outputting a first calibrated blood pressure value according to the pulse wave characteristic value and the iterative vascular elasticity coefficient. According to the embodiment of the invention, motion artifacts are effectively suppressed through differential processing of the dual-wavelength PPG sensor, the signal-to-noise ratio of signals is increased, and the problem that the blood pressure measurement error is large due to noise interference and blood vessel elastic fixation when a traditional intelligent wearable device is in a motion state is solved.

A urinary drainage system includes an air pressure apparatus. The air pressure apparatus includes a connector and an adapter. The connector includes a reduced diameter portion, a connector lumen extending from an upstream opening to a downstream opening in the reduced diameter portion, and a lateral port configured for drawing a fluid sample from the connector lumen. The adapter is sealing coupled to the connector and includes an adapter lumen receiving the reduced diameter portion, the downstream opening in fluid communication with the adapter lumen. A luminal space is defined in the adapter lumen around the reduced diameter portion of the connector. The adapter further includes an air intake port including a port lumen orthogonal to the adapter lumen, which is configured to provide a positive air flow to the luminal space to draw a fluid through the downstream opening in the reduced diameter portion of the connector.

The invention discloses a non-invasive hemodynamics monitoring method and system based on deep learning, and relates to the technical field of medical instruments, and the method comprises the steps: obtaining invasive blood flow data and non-invasive radial artery waveform data of a corresponding time point; time reference alignment is carried out on invasive blood flow data and non-invasive radial artery waveform data through time points, time drift errors between invasive and non-invasive equipment are eliminated, an initial non-invasive detection model is constructed, the method better fits the actual state of non-invasive detection, non-invasive feature vectors are used as input features after vascular elasticity compensation processing, and the non-invasive detection accuracy is improved. The initial non-invasive detection model is trained by taking blood flow parameters in the invasive data set as supervision annotation data, so that the consistency of model output and real invasive blood flow parameters is improved, 'waveform fragment-blood flow parameter 'space-time mapping is established, the running dynamic state of the non-invasive detection model is evaluated and analyzed, and the detection accuracy is improved. The performance change of the model in the training and running process can be monitored in real time, and convergence, over-fitting and under-fitting problems can be found in time.

The invention relates to the technical field of coating surface preparation, in particular to an anticoagulant coating based on novel tick-derived anticoagulant protein Qinghaenin and a preparation method of the anticoagulant coating. The functional layer of the anticoagulant coating comprises the following components: anticoagulant protein Qinghaenin or a functional peptide fragment Qinghaenin 167-192 of the anticoagulant protein Qinghaenin, wherein the amino acid sequence of the functional peptide fragment is as shown in SEQ ID NO. 2. The preparation method of the anticoagulant coating comprises the following steps: by using a polydopamine coating as a substrate layer, covalently grafting through an amido bond, immobilizing anticoagulant protein Qinghaenin capable of inhibiting FXII factor activation or a functional peptide fragment Qinghaenin 167-192 thereof on the surface of a medical polymer material, and successfully constructing a novel anticoagulant coating. Compared with an unmodified medical polymer material, the modified coating can significantly enhance the hydrophilic performance of the material and inhibit platelet adhesion and activation, finally effectively prolongs the in-vitro blood coagulation time, and shows excellent anticoagulation performance.

The invention belongs to the technical field of medical equipment. The endoscopic surgery operation quality real-time quantitative evaluation system comprises an endoscopic camera probe used for collecting endoscopic images and an endoscopic handle used for operation. The displacement sensor is integrated on the endoscope camera probe and is used for detecting the endoscope entering speed; the pressure sensor is integrated on the gas injection pipeline and is used for detecting the intracavity pressure; the force sensor is integrated on the endoscope handle and is used for detecting the tissue traction deformation; the optical coherence layer scanning probe is integrated on the endoscope camera probe and used for detecting the thickness of the submucous membrane, and the processing terminal is used for conducting real-time quantitative evaluation on the endoscopic surgery operation quality according to the endoscope entering speed, the intracavity pressure, the thickness of the submucous membrane, the tissue traction deformation image, the included angle between an instrument and a focus normal and the complication response time. According to the invention, full-process datamation real-time accurate evaluation of operation skills and operation safety of operators is realized.

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and / or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and / or dynamically identify one or more features, such as plaque and vessels, and / or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and / or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and / or quantified parameters.

The invention relates to a device (150) for monitoring the state of health of a patient (100), wherein the device (150) comprises an input interface (160) for inputting a first pressure signal (145) and a second pressure signal (155) and a processing unit (165) for processing the first pressure signal (145) and the second pressure signal (155) in order to determine a processing value (170) in order to monitor the state of health of the patient (100) based the processing value (170).

The invention provides a multi-parameter collaborative cardiovascular health monitoring system and method, and the system comprises a millimeter wave radar collection module which is used for collecting a multi-dimensional physiological signal of a target user; the third-stage signal processing module is used for carrying out noise reduction processing on the multi-dimensional physiological signals and carrying out layered feature extraction on the multi-dimensional physiological signals subjected to noise reduction to obtain multi-dimensional physiological feature parameters; and the fourth-order crowd adaptation AI evaluation module is used for carrying out crowd segmentation on the target user to obtain segmented crowds, dynamically adjusting the weight ratio of each feature parameter in the multi-dimensional physiological feature parameters according to the segmented crowds to obtain dynamic adjustment feature parameters, and carrying out blood pressure calculation, angiosclerosis calculation and vascular risk prediction according to the dynamic adjustment feature parameters. And obtaining a blood vessel health monitoring result. According to the embodiment of the invention, through software optimization and measurement technology expansion, the cardiovascular health monitoring accuracy and the application range are further improved.

The invention relates to the technical field of medical monitoring, and particularly discloses a pain degree assessment method and system based on multi-modal sensing and wearable equipment. The method comprises the following steps: acquiring physiological signals and limb movement data of a patient to form a multi-dimensional pain feature vector; a dynamic weight distribution algorithm is adopted, and physiological and limb action modal weight coefficients are adjusted in real time based on each modal data prediction confidence coefficient; a multi-modal classifier is utilized, features are fused through a cross-modal attention mechanism, and 0-10 levels of pain quantized values are output; and intelligent regulation and control of analgesia parameters are realized. The system comprises a multi-modal sensing module, a feature extraction module, a dynamic weight distribution module, a multi-modal classification module and an analgesia equipment control module. The wearable device integrates a sensor and a processing unit to realize data acquisition and analysis. According to the invention, the dynamic, precise and intelligent pain assessment is realized, the technical problems of strong subjectivity and poor real-time performance of the traditional assessment method are solved, and reliable technical support is provided for clinical analgesia management.

A multi-directional bending adjustment delivery device (100) and a valve delivery system. The present invention relates to the technical field of medical instruments and devices. The multi-directional bending adjustment delivery device (100) comprises a catheter assembly (200). The catheter assembly (200) comprises a bending adjustment tube (210). The bending adjustment tube (210) comprises a bending adjustment portion (211) and a straightening portion (212) that are rotatably connected to each other. The bending adjustment portion (211) comprises a plurality of snake bone units (2111) connected end to end. One end of each of the snake bone units (2111) is provided with a pair of first connecting lugs (2113), and the other end is provided with a pair of second connecting lugs (2114). Adjacent snake bone units (2111) are pivotally connected to each other by means of the first connecting lugs (2113) and the second connecting lugs (2114). The included angle between the line connecting the centers of the two first connecting lugs (2113) and the line connecting the centers of the two second connecting lugs (2114) of the same snake bone unit (2111) is 0-90°.