There is provided a learning device, including a learning unit that learns output related to a target feature point to be observed in a repetition section observed periodically, with the use of the first sensor data being acquired by the first system and having a time length corresponding to the repetition section, as learning data, and of teacher data based on the second sensor data acquired by the second system at a time point when a specific period of time has elapsed since a start time point of the time length related to the first sensor data, the second system being less affected by noises than the first system, in which the specific period of time is set on the basis of a time length from a start time point of the repetition section to a time point at which the target feature point is expected to appear.

Methods, apparatuses, and systems for robotic insertion of a screw, a rod, or another component of a surgical implant into a patient are disclosed. Clinical data from previous surgical procedures or information received from a supervising surgeon can be leveraged to minimize the risk of harm to the patient and improve outcomes. The methods disclosed thus provide more precise placement of implanted surgical components and implants.

Described herein are methods, devices, and systems that monitor heart rate and/or for arrhythmic episodes based on sensed intervals that can include true R-R intervals as well as over-sensed R-R intervals. True R-R intervals are initially identified from an ordered list of the sensed intervals by comparing individual sensed intervals to a sum of an immediately preceding two intervals, and/or an immediately following two intervals. True R-R intervals are also identified by comparing sensed intervals to a mean or median of durations of sensed intervals already identified as true R-R intervals. Individual intervals in a remaining ordered list of sensed intervals (from which true R-R intervals have been removed) are classified as either a short interval or a long interval, and over-sensed R-R intervals are identified based on the results thereof. Such embodiments can be used, e.g., to reduce the reporting of and/or inappropriate responses to false positive tachycardia detections.

Systems and methods for detecting arrhythmias in cardiac activity are provided and include memory to store specific executable instructions. One or more processors are configured to execute the specific executable instructions for obtaining first and second far field cardiac activity (CA) data sets over primary and secondary sensing channels, respectively, in connection with a series of beats. The system detects candidate atrial features from the second CA data set, identifies ventricular features from the first CA data set and utilizes the ventricular features to separate beat segments within the second CA data set. The system automatically iteratively analyzes the beat segments by overlaying an atrial activity search window with the second CA data set and determines whether one or more of the candidate atrial features occur within the atrial activity search window. The system adjusts an atrial sensitivity profile based on whether the atrial activity search window includes the one or more of the candidate atrial features and detects atrial events based on the atrial sensitivity profile.

Systems and methods for detecting arrhythmias in cardiac activity are provided and include memory to store specific executable instructions. One or more processors are configured to execute the specific executable instructions for obtaining first and second far field cardiac activity (CA) data sets over primary and secondary sensing channels, respectively, in connection with a series of beats. The system detects candidate atrial features from the second CA data set, identifies ventricular features from the first CA data set and utilizes the ventricular features to separate beat segments within the second CA data set. The system automatically iteratively analyzes the beat segments by overlaying an atrial activity search window with the second CA data set and determines whether one or more of the candidate atrial features occur within the atrial activity search window. The system adjusts an atrial sensitivity profile based on whether the atrial activity search window includes the one or more of the candidate atrial features and detects atrial events based on the atrial sensitivity profile.

According to the present invention, a filtering apparatus includes an FIR filter that has multipliers arranged to multiply input digital data having their respective different input time points by respective variable tap coefficients. The variable tap coefficients are each switched from a first tap coefficient to a second tap coefficient sequentially for the input digital data from later to earlier input time points. The first tap coefficient is arranged to cause the FIR filter to serve as a low-pass filter with the cut-off frequency set at a first frequency. The second tap coefficient is arranged to cause the FIR filter to serve as a low-pass filter with the cut-off frequency set at a second frequency different from the first frequency.

A system and a method include an implantable medical device (IMD) having one or more inputs configured to receive one or more sensed signals from one or more electrodes. A plurality of filters are configured to filter the one or more sensed signals and output a plurality of filtered signals. Memory is configured to store program instructions. A processor, when executing the program instructions, is configured to receive the plurality of filtered signals, and analyze the plurality of filtered signals to determine a desired one of the plurality of filters.

Embodiments of a wearable monitoring device system can include one or more dry ECG electrodes and a processor that can be configured with one or more algorithms for detecting atrial fibrillation (AF) from sensed ECG signals sensed by the one or more dry ECG electrodes, and optionally other signals. In some embodiments the algorithms include one or more AF detection algorithms and optionally a noise detection algorithm. In some embodiments the wearable monitoring device or a remote system that receives data from the wearable medical device may calculate and/or characterize AF burden from ECG signals sensed by the one or more dry ECG electrodes.

A method of operating a storage system is provided. The method includes executing an operating system on one or more processors of a compute device that is coupled to one or more solid-state drives and executing a file system on the one or more processors of the compute device. The method includes configuring the compute device with one or more replaceable plug-ins that are specific to the one or more solid-state drives, and executing a flash translation layer on the one or more processors of the compute device, with assistance through the one or more replaceable plug-ins for reading and writing the one or more solid-state drives.

A method of operating a storage system is provided. The method includes executing an operating system on one or more processors of a compute device that is coupled to one or more solid-state drives and executing a file system on the one or more processors of the compute device. The method includes configuring the compute device with one or more replaceable plug-ins that are specific to the one or more solid-state drives, and executing a flash translation layer on the one or more processors of the compute device, with assistance through the one or more replaceable plug-ins for reading and writing the one or more solid-state drives.