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Paul V. Goode, Jr., Cherry Hill US

Paul V. Goode, Jr., Cherry Hill, NJ US

Patent application numberDescriptionPublished
20080306368SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.12-11-2008
20090012379SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.01-08-2009
20090124877SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.05-14-2009
20090124878SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.05-14-2009
20100041971IMPLANTABLE ANALYTE SENSOR - An implantable analyte sensor including a sensing region for measuring the analyte and a non-sensing region for immobilizing the sensor body in the host. The sensor is implanted in a precisely dimensioned pocket to stabilize the analyte sensor in vivo and enable measurement of the concentration of the analyte in the host before and after formation of a foreign body capsule around the sensor. The sensor further provides a transmitter for RF transmission through the sensor body, electronic circuitry, and a power source optimized for long-term use in the miniaturized sensor body.02-18-2010
20100063373CALIBRATION TECHNIQUES FOR A CONTINUOUS ANALYTE SENSOR - Disclosed herein are systems and methods for calibrating a continuous analyte sensor, such as a continuous glucose sensor. One such system utilizes one or more electrodes to measure an additional analyte. Such measurements may provide a baseline or sensitivity measurement for use in calibrating the sensor. Furthermore, baseline and/or sensitivity measurements may be used to trigger events such as digital filtering of data or suspending display of data.03-11-2010
20100168540SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-01-2010
20100168541SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-01-2010
20100168542SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-01-2010
20100168543SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-01-2010
20100168544SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-01-2010
20100168657SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-01-2010
20100174167SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-08-2010
20100174168SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-08-2010
20100179399SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-15-2010
20100179402SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA FOR SENSOR CALIBRATION - Systems and methods for processing sensor analyte data are disclosed, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. The sensor can be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. Reference data resulting from benchtop testing an analyte sensor prior to its insertion can be used to provide initial calibration of the sensor data. Reference data from a short term continuous analyte sensor implanted in a user can be used to initially calibrate or update sensor data from a long term continuous analyte sensor.07-15-2010
20100179405SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-15-2010
20100179406SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-15-2010
20100179407SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.07-15-2010
20100185065SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-22-2010
20100185072SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-22-2010
20100185073SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-22-2010
20100185074SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.07-22-2010
20100198035CALIBRATION TECHNIQUES FOR A CONTINUOUS ANALYTE SENSOR - Disclosed herein are systems and methods for calibrating a continuous analyte sensor, such as a continuous glucose sensor. One such system utilizes one or more electrodes to measure an additional analyte. Such measurements may provide a baseline or sensitivity measurement for use in calibrating the sensor. Furthermore, baseline and/or sensitivity measurements may be used to trigger events such as digital filtering of data or suspending display of data.08-05-2010
20100198036CALIBRATION TECHNIQUES FOR A CONTINUOUS ANALYTE SENSOR - Disclosed herein are systems and methods for calibrating a continuous analyte sensor, such as a continuous glucose sensor. One such system utilizes one or more electrodes to measure an additional analyte. Such measurements may provide a baseline or sensitivity measurement for use in calibrating the sensor. Furthermore, baseline and/or sensitivity measurements may be used to trigger events such as digital filtering of data or suspending display of data.08-05-2010
20100214104SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.08-26-2010
20100217106SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.08-26-2010
20100217557SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.08-26-2010
20100234707SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.09-16-2010
20100234796SYSTEM AND METHODS FOR PROCESSING ANALYTE SENSOR DATA - Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor.09-16-2010
20100235106SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.09-16-2010
20100240975SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.09-23-2010
20100240976SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.09-23-2010
20100331648CALIBRATION TECHNIQUES FOR A CONTINUOUS ANALYTE SENSOR - Disclosed herein are systems and methods for calibrating a continuous analyte sensor, such as a continuous glucose sensor. One such system utilizes one or more electrodes to measure an additional analyte. Such measurements may provide a baseline or sensitivity measurement for use in calibrating the sensor. Furthermore, baseline and/or sensitivity measurements may be used to trigger events such as digital filtering of data or suspending display of data.12-30-2010
20100331655CALIBRATION TECHNIQUES FOR A CONTINUOUS ANALYTE SENSOR - Disclosed herein are systems and methods for calibrating a continuous analyte sensor, such as a continuous glucose sensor. One such system utilizes one or more electrodes to measure an additional analyte. Such measurements may provide a baseline or sensitivity measurement for use in calibrating the sensor. Furthermore, baseline and/or sensitivity measurements may be used to trigger events such as digital filtering of data or suspending display of data.12-30-2010
20110118579SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.05-19-2011
20110118580SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.05-19-2011
20110124997SYSTEM AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.05-26-2011
20110125410SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.05-26-2011
20110130970SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.06-02-2011
20110130971SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.06-02-2011
20110130998SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.06-02-2011
20110137601SYSTEMS AND METHODS FOR REPLACING SIGNAL ARTIFACTS IN A GLUCOSE SENSOR DATA STREAM - Systems and methods for minimizing or eliminating transient non-glucose related signal noise due to non-glucose rate limiting phenomenon such as ischemia, pH changes, temperatures changes, and the like. The system monitors a data stream from a glucose sensor and detects signal artifacts that have higher amplitude than electronic or diffusion-related system noise. The system replaces some or the entire data stream continually or intermittently including signal estimation methods that particularly address transient signal artifacts. The system is also capable of detecting the severity of the signal artifacts and selectively applying one or more signal estimation algorithm factors responsive to the severity of the signal artifacts, which includes selectively applying distinct sets of parameters to a signal estimation algorithm or selectively applying distinct signal estimation algorithms.06-09-2011

Patent applications by Paul V. Goode, Jr., Cherry Hill, NJ US