Patents Assigned to ANALYTICS FOR LIFE
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Patent number: 10672518Abstract: Exemplified method and system facilitates monitoring and/or evaluation of disease or physiological state using mathematical analysis and machine learning analysis of a biopotential signal collected from a single electrode. The exemplified method and system creates, from data of a singularly measured biopotential signal, via a mathematical operation (i.e., via numeric fractional derivative calculation of the signal in the frequency domain), one or more mathematically-derived biopotential signals (e.g., virtual biopotential signals) that is used in combination with the measured biopotential signals to generate a multi-dimensional phase-space representation of the body (e.g., the heart). By mathematically modulating (e.g.Type: GrantFiled: March 5, 2018Date of Patent: June 2, 2020Assignee: Analytics For Life Inc.Inventors: Timothy Burton, Shyamlal Ramchandani, Sunny Gupta
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Patent number: 10566091Abstract: Exemplified method and system facilitates monitoring and/or evaluation of disease or physiological state using mathematical analysis and machine learning analysis of a biopotential signal collected from a single electrode. The exemplified method and system creates, from data of a singularly measured biopotential signal, via a mathematical operation (i.e., via numeric fractional derivative calculation of the signal in the frequency domain), one or more mathematically-derived biopotential signals (e.g., virtual biopotential signals) that is used in combination with the measured biopotential signals to generate a multi-dimensional phase-space representation of the body (e.g., the heart). By mathematically modulating (e.g.Type: GrantFiled: March 5, 2018Date of Patent: February 18, 2020Assignee: Analytics For Life Inc.Inventors: Timothy Burton, Shyamlal Ramchandani, Sunny Gupta
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Patent number: 10566092Abstract: Exemplified method and system facilitates monitoring and/or evaluation of disease or physiological state using mathematical analysis and machine learning analysis of a biopotential signal collected from a single electrode. The exemplified method and system creates, from data of a singularly measured biopotential signal, via a mathematical operation (i.e., via numeric fractional derivative calculation of the signal in the frequency domain), one or more mathematically-derived biopotential signals (e.g., virtual biopotential signals) that is used in combination with the measured biopotential signals to generate a multi-dimensional phase-space representation of the body (e.g., the heart). By mathematically modulating (e.g.Type: GrantFiled: March 5, 2018Date of Patent: February 18, 2020Assignee: Analytics For Life Inc.Inventors: Timothy Burton, Shyamlal Ramchandani, Sunny Gupta
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Patent number: 10542897Abstract: The present disclosure facilitates capture of biosignal such as biopotential signals in microvolts, or sub-microvolts, resolutions that are at, or significantly below, the noise-floor of conventional electrocardiographic and biosignal acquisition instruments. In some embodiments, the exemplified system disclosed herein facilitates the acquisition and recording of wide-band phase gradient signals (e.g., wide-band cardiac phase gradient signals, wide-band cerebral phase gradient signals) that are simultaneously sampled, in some embodiments, having a temporal skew less than about 1 ?s, and in other embodiments, having a temporal skew not more than about 10 femtoseconds. Notably, the exemplified system minimizes non-linear distortions (e.g., those that can be introduced via certain filters) in the acquired wide-band phase gradient signal so as to not affect the information therein.Type: GrantFiled: August 26, 2016Date of Patent: January 28, 2020Assignee: Analytics For Life Inc.Inventors: Sunny Gupta, Don Crawford, Timothy Burton, Shyamlal Ramchandani, Kristine Canavan
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Patent number: 10441216Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.Type: GrantFiled: March 20, 2018Date of Patent: October 15, 2019Assignee: ANALYTICS FOR LIFE INC.Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
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Patent number: 10383535Abstract: Methods and systems for evaluating the electrical activity of the heart to identify novel ECG patterns closely linked to the subsequent development of serious heart rhythm disturbances and fatal cardiac events. Two approaches are describe, for example a model-based analysis and space-time analysis, which are used to study the dynamical and geometrical properties of the ECG data. In the first a model is derived using a modified Matching Pursuit (MMP) algorithm. Various metrics and subspaces are extracted to characterize the risk for serious heart rhythm disturbances, sudden cardiac death, other modes of death, and all-cause mortality linked to different electrical abnormalities of the heart. In the second method, space-time domain is divided into a number of regions (e.g., 12 regions), the density of the ECG signal is computed in each region and input to a learning algorithm to associate them with these events.Type: GrantFiled: March 30, 2018Date of Patent: August 20, 2019Assignee: Analytics For Life Inc.Inventors: Sunny Gupta, Mohsen Najafi Yazdi, Timothy William Fawcett Burton, Shyamlal Ramchandani, Derek Vincent Exner
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Patent number: 10362951Abstract: The present disclosure uses physiological data, ECG signals as an example, to evaluate cardiac structure and function in mammals. Two approaches are presented, e.g., a model-based analysis and a space-time analysis. The first method uses a modified Matching Pursuit (MMP) algorithm to find a noiseless model of the ECG data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to image and characterize cardiovascular tissues using complex-sub-harmonic-frequencies (CSF) quasi-periodic and other mathematical methods. In the second method, space-time domain is divided into a number of regions, the density of the ECG signal is computed in each region and inputted into a learning algorithm to image and characterize the tissues.Type: GrantFiled: April 24, 2018Date of Patent: July 30, 2019Assignee: Analytics For Life Inc.Inventors: Sunny Gupta, Mohsen Najafi Yazdi, Timothy William Fawcett Burton, Shyamlal Ramchandani, Derek Vincent Exner
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Patent number: 10362950Abstract: The present disclosure facilitates the evaluation of wide-band phase gradient information of the heart tissue to assess, e.g., the presence of heart ischemic heart disease. Notably, the present disclosure provides an improved and efficient method to identify and risk stratify coronary stenosis of the heart using a high resolution and wide-band cardiac gradient obtained from the patient. The patient data are derived from the cardiac gradient waveforms across one or more leads, in some embodiments, resulting in high-dimensional data and long cardiac gradient records that exhibit complex nonlinear variability. Space-time analysis, via numeric wavelet operators, is used to study the morphology of the cardiac gradient data as a phase space dataset by extracting dynamical and geometrical properties from the phase space dataset.Type: GrantFiled: June 26, 2017Date of Patent: July 30, 2019Assignee: Analytics For Life Inc.Inventors: Sunny Gupta, Shyamlal Ramchandani, Timothy Burton, William Sanders, Ian Shadforth
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Patent number: 10292596Abstract: Exemplified methods and systems facilitate presentation of data derived from measurements of the heart in a non-invasive procedure (e.g., via phase space tomography analysis). In particular, the exemplified methods and systems facilitate presentation of such measurements in a graphical user interface, or “GUI” (e.g., associated with a healthcare provider web portal to be used by physicians, researchers, or patients, and etc.) and/or in a report for diagnosis of heart pathologies and disease. The presentation facilitates a unified and intuitive visualization that includes three-dimensional visualizations and two-dimensional visualizations that are concurrently presented within a single interactive interface and/or report.Type: GrantFiled: September 21, 2017Date of Patent: May 21, 2019Assignee: Analytics For Life Inc.Inventors: Ian Shadforth, Meng Lei, Timothy Burton, Don Crawford, Sunny Gupta, Paul Douglas Souza, Cody James Wackerman, Andrew Hugh Dubberly
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Patent number: 10039468Abstract: The present disclosure generally relates to systems and method of a noninvasive electrocardiographic (ECG) technique for characterizing cardiac chamber size and cardiac mechanical function. A mathematical analysis of three-dimensional (3D) high resolution ECG data may be used to estimate chamber size and cardiac mechanical function. For example, high-resolution mammalian ECG signals are analyzed across multiple leads, as 3D orthogonal (X,Y,Z) or 10-channel data for 30 to 1400 seconds to derive estimates of cardiac chamber size and cardiac mechanical function. Multiple mathematical approaches may be used to analyze the dynamical and geometrical properties of the ECG data.Type: GrantFiled: November 12, 2013Date of Patent: August 7, 2018Assignee: Analytics For Life Inc.Inventors: Sunny Gupta, Timothy William Fawcett Burton, Shyamlal Ramchandani, Derek Vincent Exner
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Patent number: 9968275Abstract: The present disclosure uses physiological data, ECG signals as an example, to evaluate cardiac structure and function in mammals. Two approaches are presented, e.g., a model-based analysis and a space-time analysis. The first method uses a modified Matching Pursuit (MMP) algorithm to find a noiseless model of the ECG data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to image and characterize cardiovascular tissues using complex-sub-harmonic-frequencies (CSF) quasi-periodic and other mathematical methods. In the second method, space-time domain is divided into a number of regions, the density of the ECG signal is computed in each region and inputted into a learning algorithm to image and characterize the tissues.Type: GrantFiled: May 5, 2017Date of Patent: May 15, 2018Assignee: Analytics For Life Inc.Inventors: Sunny Gupta, Mohsen Najafi Yazdi, Timothy William Fawcett Burton, Shyamlal Ramchandani, Derek Vincent Exner
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Patent number: 9968265Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.Type: GrantFiled: February 12, 2015Date of Patent: May 15, 2018Assignee: ANALYTICS FOR LIFEInventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
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Patent number: 9955883Abstract: Methods and systems for evaluating the electrical activity of the heart to identify novel ECG patterns closely linked to the subsequent development of serious heart rhythm disturbances and fatal cardiac events. Two approaches are describe, for example a model-based analysis and space-time analysis, which are used to study the dynamical and geometrical properties of the ECG data. In the first a model is derived using a modified Matching Pursuit (MMP) algorithm. Various metrics and subspaces are extracted to characterize the risk for serious heart rhythm disturbances, sudden cardiac death, other modes of death, and all-cause mortality linked to different electrical abnormalities of the heart. In the second method, space-time domain is divided into a number of regions (e.g., 12 regions), the density of the ECG signal is computed in each region and input to a learning algorithm to associate them with these events.Type: GrantFiled: July 11, 2016Date of Patent: May 1, 2018Assignee: Analytics for Life Inc.Inventors: Sunny Gupta, Mohsen Najafi Yazdi, Timothy William Fawcett Burton, Shyamlal Ramchandani, Derek Vincent Exner
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Patent number: 9910964Abstract: Exemplified method and system facilitates monitoring and/or evaluation of disease or physiological state using mathematical analysis and machine learning analysis of a biopotential signal collected from a single electrode. The exemplified method and system creates, from data of a singularly measured biopotential signal, via a mathematical operation (i.e., via numeric fractional derivative calculation of the signal in the frequency domain), one or more mathematically-derived biopotential signals (e.g., virtual biopotential signals) that is used in combination with the measured biopotential signals to generate a multi-dimensional phase-space representation of the body (e.g., the heart). By mathematically modulating (e.g.Type: GrantFiled: June 24, 2016Date of Patent: March 6, 2018Assignee: Analytics For LifeInventors: Timothy Burton, Shyamlal Ramchandani, Sunny Gupta
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Patent number: 9737229Abstract: The present disclosure generally relates to systems and methods of a noninvasive technique for characterizing cardiac chamber size and cardiac mechanical function. A mathematical analysis of three-dimensional (3D) high resolution data may be used to estimate chamber size and cardiac mechanical function. For example, high-resolution mammalian signals are analyzed across multiple leads, as 3D orthogonal (X,Y,Z) or 10-channel data, for 30 to 800 seconds, to derive estimates of cardiac chamber size and cardiac mechanical function. Multiple mathematical approaches may be used to analyze the dynamical and geometrical properties of the data.Type: GrantFiled: June 4, 2014Date of Patent: August 22, 2017Assignee: Analytics for LifeInventors: Sunny Gupta, Derek Exner, Mohsen Najafi Yazdi, Timothy William Fawcett Burton, Shyamlal Ramchandani
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Patent number: D810947Type: GrantFiled: April 25, 2016Date of Patent: February 20, 2018Assignee: Analytics For LifeInventors: Cinnamon Larson, Terrance Ransbury
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Patent number: D843382Type: GrantFiled: September 21, 2016Date of Patent: March 19, 2019Assignee: Analytics for LifeInventors: Ian Shadforth, Meng Lei, Timothy Burton, Don Crawford, Sunny Gupta, Paul Douglas Souza, Cody James Wackerman, Andrew Hugh Dubberly
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Patent number: D855064Type: GrantFiled: September 21, 2016Date of Patent: July 30, 2019Assignee: Analytics for Life Inc.Inventor: Meng Lei
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Patent number: D858532Type: GrantFiled: September 21, 2016Date of Patent: September 3, 2019Assignee: Analytics for Life Inc.Inventor: Meng Lei
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Patent number: D880501Type: GrantFiled: February 7, 2019Date of Patent: April 7, 2020Assignee: Analytics for Life Inc.Inventors: Ian Shadforth, Meng Lei, Timothy Burton, Don Crawford, Sunny Gupta, Paul Douglas Souza, Cody James Wackerman, Andrew Hugh Dubberly