14 results about "Decompensation" patented technology

The invention relates to a chronic heart failure dynamic course evolution prediction model construction method. Comprising the following steps: uniformly mapping continuous variables including LVEF and heart rate and event variables into a time trajectory frame through an event alignment and time domain nesting strategy; using a local change rate algorithm to identify inflection points including states before acute deterioration and intervention reactions in the course of disease of each patient; constructing a state fragment set for supporting hierarchical modeling in an evolution stage; a bidirectional fusion method of trajectory clustering and medical knowledge embedding is used to construct a state space with clinical interpretability including a compensation period, edge decompensation and an acute deterioration period; taking the trajectory vector as a main input, taking a state space as a prediction target, and introducing a dual-channel structure; predicting a future path based on the current state; the disease course track change of early medication / non-hospitalization / treatment scheme change is simulated; a doctor is supported to deduce a result; the change of the output state is analyzed through perturbation of the current trajectory, and key variables are found out.

This disclosure is directed to devices, systems, and techniques for determining when to deploy sensors. Processing circuitry of an example medical device system is configured to receive first sensor data. The processing circuitry is configured to determine, based on the first sensor data, a likelihood that a heart failure decompensation event of a patient is impending. The processing circuitry is configured to compare the likelihood to a first threshold. The processing circuitry is configured to, based on the likelihood satisfying the first threshold, at least one of a) generate a first instruction for output to a user to deploy one or more biochemical or bacterial sensors, or b) control an implantable medical device to automatically deploy one or more biochemical or bacterial sensors.

A method and system for detecting risk of heart failure decompensation of a patient receives both weight information of the patient and foot temperature information of the patient. Using that received information, the method / system determines whether a change in weight and foot temperature indicates a pattern indicative of heart failure decompensation. Next, the method produces output information indicating a result of that determination.

A method and system for detecting risk of heart failure decompensation of a patient receives both weight information of the patient and foot temperature information of the patient. Using that received information, the method / system determines whether a change in weight and foot temperature indicates a pattern indicative of heart failure decompensation. Next, the method produces output information indicating a result of that determination.

Systems and methods of monitoring a patient. Exemplary methods include receiving sensor data associated with the patient from a plurality of sensors of a patient monitoring device and determining whether the sensor data satisfies one or more trigger conditions. For each of the trigger conditions satisfied, one or more messages are sent to at least one of the patient monitoring device and an external computing device for display thereby to at least one of the patient, a caregiver, and a support person. Satisfaction of one or more of the trigger conditions may indicate the patient has edema and / or is trending toward decompensation. The sensor data may have been collected from a heart rate sensor, an oximeter, an accelerometer, and / or a sensor configured to detect a distance around a limb of a patient. In some embodiments, the trigger conditions are provided by the patient, caregiver, and / or support person.

The present application relates to the technical field of medical artificial intelligence, and more particularly to a method for detecting critical multiple bone trauma based on AI. The method integrates physiological monitoring and image data of the patient, extracts the fracture site and constructs a whole-body bleeding risk distribution map, performs correlation analysis on hemoglobin changes to locate the bleeding source, and predicts the decompensation time window through the coagulation state trajectory. The above features are input into the decision model to simulate the physiological evolution path of different treatment schemes and calculate the risk, and finally output the treatment scheme with the lowest adverse probability and the decision time node. The present application realizes dynamic quantitative evaluation and optimized decision support of the detection results of the bleeding risk of critical multiple bone trauma.

A apparatus and method to treat patients with acute decompensated heart failure (ADHF), heart failure or another fluid overload condition, that includes: administrating a diuretic to the patient to increase urine output of the patient; monitoring a rate or amount of urine output by the patient after administration of the diuretic; infusing a hydration liquid into the patient to induce an increase in the urine output; and adjusting the rate or amount of the hydration liquid infused into the patient to achieve a target fluid loss in the patient.

Techniques for obtaining impedance data to provide an early warning for heart failure decompensation are described. An example device may be configured to measure subcutaneous impedance values, and increment an impedance score. In some examples, the device may use an adaptive threshold and fluid index in incrementing the impedance score. In some examples, the impedance score is compared to a threshold to determine a heart failure status of a patient. In some examples, may cause resets in fluid index values and / or determine positions or orientations of the device when determining the impedance score.

The application provides a rehabilitation nursing risk early warning system, a fatigue risk early warning method, equipment and a medium. The three-axis acceleration signals and the surface electromyography signals of a target muscle of a patient during rehabilitation nursing are synchronously collected. The surface electromyography signals are filtered according to the frequency spectrum characteristics of the three-axis acceleration signals to suppress artifacts generated by limb macro-movement, and a pre-processed electromyography signal is obtained. The median frequency sequence and the approximate entropy sequence of the amplitude envelope of the pre-processed electromyography signal are determined in a continuous sliding time window. A risk index of a muscle fatigue state is constructed according to the cooperative change relationship between the median frequency sequence and the approximate entropy sequence. The risk index is combined with a pre-set fatigue risk threshold to generate a fatigue risk early warning report of the patient during rehabilitation nursing. The scheme of the application can distinguish between normal physiological fatigue and abnormal neuromuscular decompensation.

Systems and methods of monitoring a patient. Exemplary methods include receiving sensor data associated with the patient from a plurality of sensors of a patient monitoring device and determining whether the sensor data satisfies one or more trigger conditions. For each of the trigger conditions satisfied, one or more messages are sent to at least one of the patient monitoring device and an external computing device for display thereby to at least one of the patient, a caregiver, and a support person. Satisfaction of one or more of the trigger conditions may indicate the patient has edema and / or is trending toward decompensation. The sensor data may have been collected from a heart rate sensor, an oximeter, an accelerometer, and / or a sensor configured to detect a distance around a limb of a patient. In some embodiments, the trigger conditions are provided by the patient, caregiver, and / or support person.

Techniques are described for acquiring impedance data to provide early warning of decompensated heart failure. An example device can be configured to measure subcutaneous impedance values and increase an impedance score. In some examples, the device can use an adaptive threshold and a fluid index in increasing the impedance score. In some examples, the impedance score is compared to a threshold to determine a heart failure status of a patient.

The invention provides a risk early warning system for rehabilitation nursing, a fatigue risk early warning method, equipment and a medium. The method comprises the following steps: synchronously acquiring a three-axis acceleration signal and a surface electromyogram signal of a target muscle of a patient during rehabilitation nursing; carrying out filtering processing on the surface electromyographic signals according to frequency spectrum characteristics of the three-axis acceleration signals so as to suppress artifacts generated by macroscopic movement of limbs, and obtaining preprocessed electromyographic signals; determining a median frequency sequence of the preprocessed electromyographic signals and an approximate entropy sequence of amplitude envelope in a continuously sliding time window; constructing a risk index of the muscle fatigue state according to a collaborative change relation between the median frequency sequence and the approximate entropy sequence; and generating a fatigue risk early warning report of the patient during rehabilitation nursing by combining the risk index with a preset fatigue risk threshold. By adopting the scheme of the invention, a normal physiological fatigue process and an abnormal neuromuscular decompensation state can be discriminated.

Techniques for obtaining impedance data to provide an early warning for heart failure decompensation are described. An example device may be configured to measure subcutaneous impedance values, and increment an impedance score. In some examples, the device may use an adaptive threshold and fluid index in incrementing the impedance score. In some examples, the impedance score is compared to a threshold to determine a heart failure status of a patient. In some examples, may cause resets in fluid index values and / or determine positions or orientations of the device when determining the impedance score.

Cardiac load modulation systems and methods are disclosed for treatment of patients in congestive heart failure. Disclosed systems include dual occlusion, telescoping catheters allowing simultaneous or sequential occlusion in the superior vena cava and inferior vena cava to synergistically modulate heart pre-load on the right side of the heart and pressure difference in the kidneys as a potential treatment or management of acute decompensated heart failure (ADHF). Control algorithms and safety parameters for treatment with disclosed systems are also disclosed.