Comm Vault Systems, Inc.

Vivaquant LLC

Cardionomic, Inc.

Brian Brockway

Anand Prahlad

Marcus S Muller

David Ngo

Jeremy Alan Schwartz

Marina Brockway

Rajiv Kottomtharayil

Parag Gokhale

Arun Prasad Amarendran

Srinivas Kavuri

Andreas May

Alan G Bunte

Jun Lu

Garrett Charles Duffy

Deepak Raghunath Attarde

Jun H Ahn

Randy DeMeno

Rammohan G Reddy

Robert Hamlin

Steven D Goedeke

Arjun D Sharma

Jonathan Engel

Sanath Kumar

Daniel Jiang Stein

Christie J Van Wagoner

Simon Taylor

David Christopher Olson

Michael C Garrett

Anna M Brockway

Adwait Vinay Thattey

Marcus B Muller

Arun Prasad

Monitoring apparatus

Ransomware detection accuracy is improved by analyzing patterns of changes in filename extension counts, relative to each other, that occur in a file system over time. The disclosed approach is malware-agnostic and does not rely on recognizing malware extensions or on real-time monitoring of the target file system. Instead, during each successive backup job of the target file system, the disclosed technology counts different types of filename extensions and compares the counts to each other and to corresponding counts taken in earlier backup jobs. Preferably, the anomaly detection analysis uses machine learning to discern a behavior pattern of the file system, which indicates how filename extensions are distributed and how much they change between backup jobs over time.

Ransomware detection accuracy based on machine learning analysis of filename extension patterns

As may be implemented in accordance with one or more aspects depicted herein, an apparatus and/or method involves monitoring heart rhythm of a patient utilizing a housing having amplifying circuitry and digitizing circuitry configured to amplify and digitize ECG signals. Two or more legs protrude from the housing, each configured to provide an electrical connection from an ECG electrode to the amplifying circuitry. Computing circuitry processes the digitized ECG signals, communication circuitry communicates data corresponding to the ECG signals, and data storage circuitry stores data corresponding to the ECG signals. A charge storage circuit provides power to the circuitry, computing circuitry, and communication circuitry. The legs mechanically connect to skin electrodes and to support the weight of the housing and its contents in response to the skin electrodes being adhesively secured to skin.

Methods and apparatuses for monitoring ECG

Aspects of the present disclosure are directed to detecting apneic and/or hypopneic events, utilizing a physiological signal. Various apparatuses and/or methods involve computing time series of interbeat intervals are from data characterizing activity of a beating heart, decomposing the time series is into subcomponents, and identifying ones of the subcomponents that relate to a portion of the data during which an apneic and/or hypopneic, as may be detected via oximetry. Once identified, these subcomponents and related formula/weighting can be utilized in computing further subcomponents from the data, and identifying further apneic and/or hypopneic events therefrom. In this context, such events may be detected without necessarily involving further use of oximetry.

Apneic/hypopneic assessment via physiological signals

Systems and methods are described for denoising, or filtering out, unwanted noise or interference, from biological or physiological parameter signals or waveforms such as ECG signals caused by application of electromagnetic energy (e.g., electrical stimulation) in a vicinity of sensors configured to obtain the biological or physiological parameter signals.

Systems and methods for denoising physiological signals during electrical neuromodulation

Systems and methods for managing electronic data are disclosed. Various data management operations can be performed based on a metabase formed from metadata. Such metadata can be identified from an index of data interactions generated by a journaling module, and obtained from their associated data objects stored in one or more storage devices. In various embodiments, such processing of the index and storing of the metadata can facilitate, for example, enhanced data management operations, enhanced data identification operations, enhanced storage operations, data classification for organizing and storing the metadata, cataloging of metadata for the stored metadata, and/or user interfaces for managing data. In various embodiments, the metabase can be configured in different ways. For example, the metabase can be stored separately from the data objects so as to allow obtaining of information about the data objects without accessing the data objects or a data structure used by a file system.

Systems and methods for using metadata to enhance data identification operations

Aspects of the present disclosure are directed to apparatuses and methods for monitoring vital signs from a human being. Various such aspects involve an apparatus or method involving the monitoring of vital signs in a manner that facilitates enhanced characterization of physiological conditions. In many embodiments, two or more such vital signs are monitored. A signal acquisition, digitization, and computing module removing noise, extracts information useful for diagnosing a health or fitness characteristic of the human being, and/or compresses information to reduce data volume. A wireless communications circuit transmits the vital signs to a receiver.

Physiological signal monitoring and apparatus therefor

A method and system for creating an index of content without interfering with the source of the content includes an offline content indexing system that creates an index of content from an offline copy of data. The system may associate additional properties or tags with data that are not part of traditional indexing of content, such as the time the content was last available or user attributes associated with the content. Users can search the created index to locate content that is no longer available or based on the associate attributes.

Method and system for offline indexing of content and classifying stored data

Various embodiments are directed to signal processing. In accordance with example embodiments, methods and apparatuses involve using at least two electrodes that sense an ECG signal. A denoising module is communicatively coupled to the at least two electrodes, and receives the ECG signal sensed by the sensing electrodes. The denoising module includes circuitry that conditions and digitizes the ECG signal, and a computing circuit that processes the digitized ECG signal to denoise the ECG signal. A communications circuit generates a communication including the denoised ECG signal for access by a remote device.

ECG sensing with noise filtering

Aspects of the present disclosure are directed to detecting Atrial Fibrillation (AF). As may be implemented in accordance with one or more embodiments, a time series of inter-beat intervals is computed from a recording of activity of a beating heart. The time series is decomposed into subcomponents, and an envelope of at least one of the subcomponents is computed. The presence of atrial fibrillation (AF) is detected based upon characteristics of the envelope that are indicative of AF.

Method and apparatus for detection of heartbeat characteristics

Physiological signals such as ECG signals are obtained from a patient. In accordance with one or more embodiments, an apparatus, system and/or method is directed to process the digitized ECG signals (e.g., by removing noise).

System for processing physiological data

Aspects of the disclosure are directed to detecting physiological and/or other characteristics of subjects. As may be implemented in accordance with one or more embodiments, a time series of cardiac intervals is computed from a recording of activity of a beating heart of a subject, and the time series is decomposed into subcomponents. An envelope of at least one of the subcomponents is computed, and the presence and/or degree of a depressive or stressed mental state of the subject is detected based upon characteristics of the envelope.

Method and apparatus for assessing cardiac and/or mental health

Growing community of inventors

Shrewsbury, NJ, United States of America

Brian Brockway