Patent classifications
A61B5/319
System For Induction-Based Subcutaneous Insertable Physiological Monitor Recharging
An insertable cardiac monitor (ICM) with induction-based recharging capabilities and a transmitting coil for recharging the same are disclosed. The length of the monitoring performed by the ICM is extended and the functionality of the ICM enhanced, by including an internal energy harvesting module that allows for charging the ICM at a high speed without burning the patient or overheating components of the ICM. Internally, the energy harvesting module includes at least two overlapping receiving coils that are spaced to be orthogonal to each other and that have a tilt angle of substantially 45°. Such overlapping wire combination allows to minimize mutual inductance of the solenoid coils and increase the rate at which energy can be provided to the energy harvesting module. Further, the rate at which the energy is transmitted from the outside can be increased by defining in a transmitting coil a substantially triangular gap.
System For Induction-Based Subcutaneous Insertable Physiological Monitor Recharging
An insertable cardiac monitor (ICM) with induction-based recharging capabilities and a transmitting coil for recharging the same are disclosed. The length of the monitoring performed by the ICM is extended and the functionality of the ICM enhanced, by including an internal energy harvesting module that allows for charging the ICM at a high speed without burning the patient or overheating components of the ICM. Internally, the energy harvesting module includes at least two overlapping receiving coils that are spaced to be orthogonal to each other and that have a tilt angle of substantially 45°. Such overlapping wire combination allows to minimize mutual inductance of the solenoid coils and increase the rate at which energy can be provided to the energy harvesting module. Further, the rate at which the energy is transmitted from the outside can be increased by defining in a transmitting coil a substantially triangular gap.
Electrified anatomical model
An anatomical model simulator system includes an anatomical model assembly. The anatomical model assembly includes an anatomical model shell having a plurality of apertures defined therein; and a plurality of electrodes. Each electrode of the plurality of electrodes is disposed within one of the plurality of apertures, and each electrode includes at least one of carbon black and silver epoxy. The anatomical model simulator system also includes a model control system. The model control system includes a power supply configured to deliver electrical energy to the plurality of electrodes; and a controller configured to control the delivery of the electrical energy to the plurality of electrodes.
Electrified anatomical model
An anatomical model simulator system includes an anatomical model assembly. The anatomical model assembly includes an anatomical model shell having a plurality of apertures defined therein; and a plurality of electrodes. Each electrode of the plurality of electrodes is disposed within one of the plurality of apertures, and each electrode includes at least one of carbon black and silver epoxy. The anatomical model simulator system also includes a model control system. The model control system includes a power supply configured to deliver electrical energy to the plurality of electrodes; and a controller configured to control the delivery of the electrical energy to the plurality of electrodes.
Machine learning using clinical and simulated data
Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.
Machine learning using clinical and simulated data
Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.
MACHINE LEARNING USING SIMULATED CARDIOGRAMS
A system is provided for generating a classifier for classifying electromagnetic data (e.g., ECG) derived from an electromagnetic source (e.g., heart). The system accesses a computational model of the electromagnetic source. The computational model models the electromagnetic output of the electromagnetic source over time based on a source configuration (e.g., rotor location) of the electromagnetic source. The system generates, for each different source configuration (e.g., different rotor locations), a modeled electromagnetic output (e.g., ECG) of the electromagnetic source for that source configuration. For each modeled electromagnetic output, the system derives the electromagnetic data for the modeled electromagnetic output and generates a label (e.g., rotor location) for the derived electromagnetic data from the source configuration for the modeled electromagnetic data. The system trains a classifier with the derived electromagnetic data and the labels as training data. The classifier can then be used to classify the electromagnetic output collected from patients.
MACHINE LEARNING USING SIMULATED CARDIOGRAMS
A system is provided for generating a classifier for classifying electromagnetic data (e.g., ECG) derived from an electromagnetic source (e.g., heart). The system accesses a computational model of the electromagnetic source. The computational model models the electromagnetic output of the electromagnetic source over time based on a source configuration (e.g., rotor location) of the electromagnetic source. The system generates, for each different source configuration (e.g., different rotor locations), a modeled electromagnetic output (e.g., ECG) of the electromagnetic source for that source configuration. For each modeled electromagnetic output, the system derives the electromagnetic data for the modeled electromagnetic output and generates a label (e.g., rotor location) for the derived electromagnetic data from the source configuration for the modeled electromagnetic data. The system trains a classifier with the derived electromagnetic data and the labels as training data. The classifier can then be used to classify the electromagnetic output collected from patients.
AUGMENTATION OF IMAGES WITH SOURCE LOCATIONS
Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.
AUGMENTATION OF IMAGES WITH SOURCE LOCATIONS
Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.