116 results about "Patient state" patented technology

A system is provided that furnishes expert procedural guidance based upon patient-specific data gained from surgical instruments incorporating sensors on the instrument's working surface, one or more reference sensors placed about the patient, sensors implanted before, during or after the procedure, the patient's personal medical history, and patient status monitoring equipment. Embodiments include a system having a surgical instrument with a sensor for generating a signal indicative of a property of a subject tissue of the patient, which signal is converted into a current dataset and stored. A processor compares the current dataset with other previously stored datasets, and uses the comparison to assess a physical condition of the subject tissue and / or to guide a procedure being performed on the tissue.

A system and method for monitoring a patient includes a sensor configured to acquire physiological data from a patient and a processor configured to receive the physiological data from the at least one sensor. The processor is also configured to apply a spectral estimation framework that utilizes structured time-frequency representations defined by imposing, to the physiological data, a prior distributions on a time-frequency plane that enforces spectral estimates that are smooth in time and sparse in a frequency domain. The processor is further configured to perform an iteratively re-weighted least squares algorithm to perform yield a denoised time-varying spectral decomposition of the physiological data and generate a report indicating a physiological state of the patient.

A system for the detection of cardiac events occurring in a human patient is provided. At least two electrodes are included in the system for obtaining an electrical signal from a patient's heart. An electrical signal processor is electrically coupled to the electrodes for processing the electrical signal. The systems receives data regarding the patient's state (e.g. asleep, exercising). Patient state information is stored in a patient state array, thereby enabling the system to track the patient's state over time, and to select an appropriate test for detecting a cardiac event based on both past and present data regarding the patient's state.

Disclosed is a system and method of assessing the efficacy of treatment of neurological or psychological disorders. The preferred embodiment uses at least two surface electrodes to acquire EEG signals from the surface of a patient's body, a processor for computing from the EEG signals various features and indices that are representative of the patient's neurological or psychological state. Changes in these parameters may be used to assess the efficacy of treatment and to modify the treatment to optimize the resultant patient state.

Disclosed is a system and method of assessing the efficacy of and predicting response to treatment of neurological or psychological disorders. The preferred embodiment uses at least two surface electrodes to acquire EEG signals from the surface of a patient's body, a processor for computing from the EEG signals various features and indices that are representative of the patient's neurological or psychological state. Pretreatment indices represent a patient's neurological or psychological state and therefore may be used to predict the response to treatment. Changes in these parameters may be used to assess the efficacy of treatment and to modify the treatment to optimize the resultant patient state.

Optimization of evoked response detection in an automatic capture detection system employed by an implantable cardiac stimulation device is presented. Patient state information is used to determine the appropriate settings of variables that are associated with the evoked response signal detection algorithm. The variables used by the evoked response signal detection algorithm are first established for the patient in a variety of positions. During operation of the implantable cardiac stimulation device, the patient state is monitored and the variables used by the evoked response signal detection algorithm are adjusted accordingly.

Systems and methods are described for adjusting the operation of implantable stimulation devices used to provide medical monitoring and treatment. Several hierarchical algorithms are described which operate according to conditionally obtaining a patient response to an alert signal. In one such strategy semi-automatic therapy adjustment occurs by automatically issuing patient alert messages when selected operations are to occur, and using a patient's response to the alert message that is provided within a selected time limit in order to contingently adjust therapy. Methods are also described for resolving conflicts which may occur when time information and sensed data information each indicate different patient states are occurring. Although treatment of neural and cardiac disorders is emphasized, the techniques can be applied to the monitoring and treatment of any medical disorder with an implanted device.

The invention relates to a medical cloud platform data sharing system and method based on third-party service, belonging to the medical cloud platform field. The system comprises: a terminal device and a cloud platform; the cloud platform receives massive vital sign data sent by the terminal device, applies a deep learning framework of distributed parallel computing to analyze and process the massive vital signs data, screens abnormal data, sends abnormal event early warning to users and prompts medical personnel to quickly perform intervene; and the terminal device sends a command to the cloud platform, wherein the command comprises a user-defined term setting command, a real-time data service command, a data transfer command, a medical document service command, a consultation service command, a medical cooperation information publishing command, a data analysis statistics command, a patient state assessment command, a data analysis report management command and a medical tool libraryquery command, and the terminal device obtains the support of the third-party service. The medical cloud platform data sharing system and method based on third-party service improve the medical quality and the working efficiency of users and reduce the labor intensity and the work pressure of the medical workers.

A dynamic diagnostic plan generator arranges diagnostic test procedures related to a vehicle / power tool / patient symptom or operational problem in a sequence based on a probabilistic Failure Mode and Effects Analysis (FMEA). The diagnostic plan generator also tracks a vehicle / power tool / patient state, and provides instructions for test preparation steps and instructions for performing the diagnostic test procedures. The plan generator further generates schematic illustrations of the diagnostic test procedures, and creates a diagnostic data structure containing information related to the diagnostic test procedures. In addition, the diagnostic plan generator sends and receives information regarding actual failure mode occurrences, for example, to and from a central database. Furthermore, the diagnostic plan generator facilitates the creation of failure mode tests by an expert diagnostics author.

Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

The invention discloses an assistant diagnosis and treatment system based on a knowledge graph. The system comprises a database, a patient information processing module and a diagnosis and treatment scheme push module, wherein the database is used for storing the medical knowledge graph, and the knowledge graph takes medical operations as nodes and takes the patient state between every two continuous medical operations as an edge; the patient information processing module receives information of a patient, extracts historical medical operations and patient state information and sends the historical medical operations and the patient state information to the diagnosis and treatment scheme push module; the diagnosis and treatment scheme push module acquires the knowledge graph from the database, matches the patient information with the knowledge graph according to the direction indicated by the edge in the knowledge graph, determines the position of the current state, in the knowledge graph, of the patient, and pushes a to-be-detected medical index and / or the next diagnosis and treatment operation based on the knowledge graph. By means of the assistant diagnosis and treatment system,the diagnosis and treatment stage of the patient can be quickly known, and a next diagnosis and treatment advice is given.

The invention discloses an intelligent rehabilitation robot system based on a cloud platform and an operation method of the intelligent rehabilitation robot system. The system comprises a local training system and the cloud platform; the local training system comprises a robot control system, a rehabilitation robot body and an information collecting system; the cloud platform comprises a patient database, a healthy person database and a patient state evaluation system. The model and a robot control system are combined, the intelligent rehabilitation robot fusing patient intelligent evaluation is developed, the technique of a therapist is simulated, and autonomous training of patients is achieved.

The invention provides an independent column bag-type intelligent flexible automatic turnover nursing bed, belonging to the technical fields of medical care and automatic control. The independent column bag-type intelligent flexible automatic turnover nursing bed is composed of closed bag-type water storage equipment, a motor-driven pump, a water bag group, a main controller and a bed support. The automatic turnover nursing bed has the beneficial effects as follows: by means of full utilization of the thermal conductivity and incompressibility of water, accurate control of body temperature and prone position of human body can be realized by controlling water temperature as well as the pressure and flow of water bags in various units, and meanwhile the nursing bed in the operating process can keep quiet without air current noise like that of an air bag device; and as a proportional servo valve is employed for controlling water flow, water filling and discharging time of each water bag can be adjusted artificially so as to achieve the purpose of humanized control of tolerance level of patients during different periods. The automatic turnover nursing bed can regulate body temperature, flexibly change the prone position of a patient lying in bed for long term according to the acceptance of the patient, promote blood circulation, monitor the state of the patient in real time by controlling a computer and various sensors, reduce nursing workload and false accept rate of nursing personnel maximally and improve comfort level of the patient. The independent column bag-type intelligent flexible automatic turnover nursing bed has the advantages of compact structure, fewer parts, lighter weight compared with the similar device, and small packing size, and is easy to replace damaged parts, and is applicable to the environment in shortage of medical personnel for disaster relief, battlefield nursing and the like.

The invention discloses a medical system with an intelligent diagnosis function. The system is characterized by comprising a hospital system, a family system and a remote monitoring center, wherein the hospital system comprises a medical examination apparatus, a patient state grading module, an intelligent diagnosis module and a data integration server; and the family system comprises a portable monitoring apparatus.

The invention relates to a multi-function bedside nursing work station, which comprises a lower cabinet body, a strut formed by extending upwards from the top of the lower cabinet body, and an upper cabinet body supported by the strut, wherein the side of the lower cabinet body is flexibly provided with a lower cabinet door; drawers are arranged in the lower cabinet body; an electronic body temperature measuring and reading module, a tourniquet storing slot, a module with the functions of reading a mercury thermometer, sterilizing and zeroing, a blood collecting pipe agitating module, an electronic blood pressure sphygmometer and a directional illuminating lamp with adjustable brightness and position are arranged in the drawer; a call and response system and a call button connected to the call and response system are arranged in the strut; and a touch screen computer, a fingerprint registering module, a bar code scanner, a heating thermostat, an infusion monitoring module, a patient state monitoring camera, a transparent infusion bottle storing region and the upper cabinet door connected to the upper cabinet body are arranged in the upper cabinet body.

The invention belongs to a remote regulation and control method for an implanted medical device, and particularly relates to a method for remote regulation control as well as tracking survey of patient state of an implanted deep brain stimulator. The system is based on the SIP (session initiation protocol) and RTP (real-time transport protocol) as well as Bluetooth communication mode of the 3G (3rd generation) communication network, and realizes one-to-one visual safe remote regulation and control. The system mainly comprises a control end 1, a 3G mobile communication network 2, a client 3, aprogram controller 4 and an implanted pulse generator 5. The regulation and control method comprises the following steps: a doctor looks for relevant information of a patient through a computer 6 of the control end 1 and a 3G mobile phone 8, observes the physical sign of the patient, selects proper adjustment parameters and sends the adjustment parameters to the client 3 through the 3G mobile communication network 2; the client 3 communicates with the program controller 10 through a Bluetooth protocol; and the program controller 10 controls the pulse generator 11 and reversely returns the feedback information to the control end. According to the invention, the physical sign information of the patient can be acquired anytime and anywhere, the stimulation pulse parameters are adjusted, and the clinical requirements on tracking visit and quick diagnosis of the patient with the implanted deep brain stimulator are met; and moreover, as the public wireless communication network and common communication equipment are used, the cost is low, the reliability is high, and the practicability is strong.

Disclosed is a system and method of assessing the efficacy of treatment of neurological or psychological disorders. The preferred embodiment uses at least two surface electrodes to acquire EEG signals from the surface of a patient's body, a processor for computing from the EEG signals various features and indices that are representative of the patient's neurological or psychological state. Changes in these parameters may be used to assess the efficacy of treatment and to modify the treatment to optimize the resultant patient state.

The invention relates to a myocardial infarction first-aid medicine feeding robot and a working method thereof. The robot comprises the components of a robot body, a central processor arranged on therobot body, a medical box, mechanical arms, a pulley, bracelet detecting equipment which is connected with the central processor, a binocular deep camera, an infrared radar, a stepping motor and a joint servo motor. The bracelet detecting equipment performs real-time monitoring on an electrocardiogram signal of the patient and transmits the electrocardiogram signal and patient position informationto the central processor. After the central processor determines an abnormity of the electrocardiogram signal, the central processor controls the stepping motor to drive the pulley to arrive at the patient position. The binocular deep camera performs accurate identification on the attitude, face, mouth and nose of the patient. The mechanical arms assist the patient to perform medicine taking according to the patient state through driving by the joint servo motor. The myocardial infarction first-aid medicine feeding robot aims to monitor the daily electrocardiogram of a myocardial infarction alone-living patient and can perform in-time helping to the patient for taking the medicine when acute myocardial infarction of the patient occurs, thereby greatly reducing possibility of severe results caused by acute myocardial infarction of the patient.

Patient treatment may be optimized using Recurrent Neural Network (RNN) based state simulation and Reinforcement learning (RL) techniques to simulate future states and actions. A RNN state simulator and a RL action generator may be trained using patient data such as historical states and actions. The RL action generator may be optimized by applying the RNN state simulator to simulating future states and applying the RL action generator to generate recommended actions based on the simulated future states. This process may be iteratively performed until a computational convergence is reached by the RL action generator which may indicate that the RL action generator has been optimized. A patient state may be fed into the optimized RL action generator to generate an optimal recommended treatment action.

The invention discloses an intelligent medical monitoring system which is characterized in that patient sign monitoring and related data sending are achieved by means of related knowledge of the Internet of things, the patient state is automatically detected to meet the patient requirement or complete alarming, and the patient medical history and in-hospital diagnosis and treatment conditions arerecorded through big data; and the system comprises a medical bed body, a monitoring module, a data detection module, a data transmission module, a control module and an auxiliary diagnosis module, and the monitoring module is a core module of the intelligent medical monitoring system; and the state of the patient is monitored in real time through a camera, some simple gestures are set to represent different appeals of the patient and are identified through an image processing technology, and the control module converts the gestures into corresponding instructions to control a motor to complete corresponding actions or alarm. The system has the greatest advantage that non-professional medical staff can be automatically helped to take preliminary diagnosis and emergency alarm measures by detecting the environment and related parameters of the body feeling of a patient.

Provided is a remote multi-sensor monitoring medical system, characterized by comprising a hospital system, a home system, and a remote monitoring center. The hospital system comprises a medical inspection device, a patient state grading module, an intelligent diagnosis module, and a data integration server. The home system comprises a portable multi-sensor monitoring device.

Provided is a portable multi-sensor monitoring medical system. The system is characterized by comprising a hospital system, a home system and a remote monitoring center. The hospital system comprises a medical examination apparatus, a patient state classification module, an intelligent diagnostic module, and a data integration server. The home system comprises a portable multi-sensor monitoring apparatus.

The invention discloses an electric quantity detection system and method of an implantable neuro-stimulation apparatus. The method comprises the following steps that: electric parameters of an implantable neuro-stimulation apparatus as well as time changing increments corresponding to the electric parameters are obtained, wherein the electric parameters contain total voltages and a total currents of a battery and the total currents of the battery contain a simulation current and a communication current; consumed power of the battery is obtained according to the electric parameters and the corresponding time changing increments; and then the consumed power is outputted. With the system and method, various emergency situations, including influences on the electric quantity of the battery by patient states and the operating states of the implantable neuro-stimulation apparatus, of the implantable neuro-stimulation apparatus during the application process are taken into consideration. Therefore, the changing situation of the battery electric quantity can be monitored precisely in real time and thus the operator can have the better user experience on the implantable neuro-stimulation apparatus.

Infusion systems, infusion devices, and related patient monitoring systems and methods are provided. A method of monitoring a physiological condition of a patient involves obtaining, from a medical device, data indicative of a current state of the patient, obtaining a probable patient response model for the physiological condition after the current state, the probable patient response model being based on historical data associated with one or more historical patient states corresponding to the current state, optimizing an activity attribute input variable to the probable patient response model for achieving an output from the probable patient response model within a target range for the physiological condition of the patient based on the current state, and providing, on a display device, a recommendation indicating an optimal value for the activity attribute input variable.