Patents by Inventor Conner Daniel Cross Galloway
Conner Daniel Cross Galloway has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240099593Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: ApplicationFiled: December 1, 2023Publication date: March 28, 2024Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Patent number: 11915825Abstract: Disclosed systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device receives electrocardiogram data from the electrocardiogram sensor and applies a machine learning model to the received electrocardiogram data. The machine learning model has been trained based on previous electrocardiogram data of a plurality of subjects. The electrocardiogram data of the plurality of subjects have one or more associated analyte measurements. The processing device may determine an indication of a level of the analyte based on the electrocardiogram data.Type: GrantFiled: February 12, 2018Date of Patent: February 27, 2024Assignee: AliveCor, Inc.Inventors: Conner Daniel Cross Galloway, Alexander Vainius Valys, Frank Losasso Petterson, Daniel Treiman
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Patent number: 11877830Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: GrantFiled: September 24, 2019Date of Patent: January 23, 2024Assignee: ALIVECOR, INC.Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Publication number: 20210345972Abstract: Disclosed are systems for non-invasively determining a measurement of an analyte. The systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device can execute instructions to receive electrocardiogram data from the electrocardiogram sensor and apply a machine learning model, wherein the machine learning model has been trained based on previous electrocardiogram data associated with a subject and source of an analyte measurement associated with the subject. The system may also determine an indication of a level of the analyte based on the electrocardiogram data.Type: ApplicationFiled: July 21, 2021Publication date: November 11, 2021Inventors: Conner Daniel Cross Galloway, Alexander Vainius Valys, David E. Albert, Frank Losasso Petterson
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Publication number: 20210290141Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.Type: ApplicationFiled: June 8, 2021Publication date: September 23, 2021Inventors: Conner Daniel Cross Galloway, David E. Albert
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Patent number: 11103194Abstract: Disclosed are systems for non-invasively determining a measurement of an analyte. The systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device can execute instructions to receive electrocardiogram data from the electrocardiogram sensor and apply a machine learning model, wherein the machine learning model has been trained based on previous electrocardiogram data associated with a subject and source of an analyte measurement associated with the subject. The system may also determine an indication of a level of the analyte based on the electrocardiogram data.Type: GrantFiled: December 14, 2017Date of Patent: August 31, 2021Assignee: AliveCor, Inc.Inventors: Conner Daniel Cross Galloway, Alexander Vainius Valys, David E. Albert, Frank Losasso Petterson
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Patent number: 11103176Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.Type: GrantFiled: November 7, 2019Date of Patent: August 31, 2021Assignee: AliveCor, Inc.Inventors: Conner Daniel Cross Galloway, David E. Albert
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Publication number: 20200281485Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: ApplicationFiled: September 24, 2019Publication date: September 10, 2020Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Publication number: 20200138316Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.Type: ApplicationFiled: November 7, 2019Publication date: May 7, 2020Inventors: Conner Daniel Cross Galloway, David E. Albert
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Publication number: 20200107733Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: ApplicationFiled: September 24, 2019Publication date: April 9, 2020Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Patent number: 10561321Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: GrantFiled: October 5, 2018Date of Patent: February 18, 2020Assignee: AliveCor, Inc.Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Patent number: 10478084Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.Type: GrantFiled: December 21, 2015Date of Patent: November 19, 2019Assignee: AliveCor, Inc.Inventors: Conner Daniel Cross Galloway, David E. Albert
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Publication number: 20190104951Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: ApplicationFiled: October 5, 2018Publication date: April 11, 2019Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Publication number: 20190076031Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: ApplicationFiled: November 9, 2018Publication date: March 14, 2019Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Publication number: 20190038148Abstract: Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (“other-factors”) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.Type: ApplicationFiled: October 5, 2018Publication date: February 7, 2019Inventors: Alexander Vainius Valys, Frank Losasso Petterson, Conner Daniel Cross Galloway, David E. Albert, Ravi Gopalakrishnan, Lev Korzinov, Fei Wang, Euan Thomson, Nupur Srivastava, Omar Dawood, Iman Abuzeid
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Publication number: 20180233227Abstract: Disclosed systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device receives electrocardiogram data from the electrocardiogram sensor and applies a machine learning model to the received electrocardiogram data. The machine learning model has been trained based on previous electrocardiogram data of a plurality of subjects. The electrocardiogram data of the plurality of subjects have one or more associated analyte measurements. The processing device may determine an indication of a level of the analyte based on the electrocardiogram data.Type: ApplicationFiled: February 12, 2018Publication date: August 16, 2018Inventors: Conner Daniel Cross Galloway, Alexander Vainius Valys, Frank Losasso Petterson, Daniel Treiman
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Publication number: 20180160983Abstract: Disclosed are systems for non-invasively determining a measurement of an analyte. The systems include an electrocardiogram sensor and a processing device operatively coupled to the electrocardiogram sensor. The processing device can execute instructions to receive electrocardiogram data from the electrocardiogram sensor and apply a machine learning model, wherein the machine learning model has been trained based on previous electrocardiogram data associated with a subject and source of an analyte measurement associated with the subject. The system may also determine an indication of a level of the analyte based on the electrocardiogram data.Type: ApplicationFiled: December 14, 2017Publication date: June 14, 2018Inventors: Conner Daniel Cross Galloway, Alexander Vainius Valys, David E. Albert, Frank Losasso Petterson
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Publication number: 20170215756Abstract: Apparatuses and methods (including methods of using such apparatuses) for de-noising electrocardiograms (ECGs) by manually or automatically adjusting the amount of filtering of an ECG signal. For example, real-time ECG signals may be filtered by combining in a weighted fashion an unfiltered portion of an ECG (or a filtered portion of the same ECG) with the same portion of the ECG that has been filtered. The weighting may be adjusted manually and/or automatically. Also described herein are methods for real-time filtering of ECG signals using a combination of filtering techniques including filtering to correct baseline wander, Savitzky-Golay denoising, and threshold smoothing. Multiple filtering techniques may be combined in a weighed manner to provide signal de-noising.Type: ApplicationFiled: April 21, 2017Publication date: August 3, 2017Inventors: Conner Daniel Cross GALLOWAY, Alexander Vainius VALYS, Nicholas Peter HUGHES, David E. ALBERT
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Patent number: 9681814Abstract: Apparatuses and methods (including methods of using such apparatuses) for de-noising electrocardiograms (ECGs) by manually or automatically adjusting the amount of filtering of an ECG signal. For example, real-time ECG signals may be filtered by combining in a weighted fashion an unfiltered portion of an ECG (or a filtered portion of the same ECG) with the same portion of the ECG that has been filtered. The weighting may be adjusted manually and/or automatically. Also described herein are methods for real-time filtering of ECG signals using a combination of filtering techniques including filtering to correct baseline wander, Savitzky-Golay denoising, and threshold smoothing. Multiple filtering techniques may be combined in a weighed manner to provide signal de-noising.Type: GrantFiled: December 18, 2015Date of Patent: June 20, 2017Assignee: Alivecor, Inc.Inventors: Conner Daniel Cross Galloway, Alexander Vainius Valys, Nicholas Peter Hughes, David E. Albert
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Patent number: D920990Type: GrantFiled: November 21, 2017Date of Patent: June 1, 2021Assignee: AliveCor, Inc.Inventors: Melissa McClean, Alexander Vainius Valys, Conner Daniel Cross Galloway, Vivek P. Gundotra, Frank Losasso Petterson