Patents by Inventor Scott Pappada
Scott Pappada 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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Patent number: 11864896Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.Type: GrantFiled: March 25, 2019Date of Patent: January 9, 2024Assignee: Aptima, Inc.Inventors: Kevin Durkee, Scott Pappada, Andres Ortiz, William DePriest, John Feeney, Alexandra Geyer, Seamus Sullivan, Sterling Wiggins
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Patent number: 11532241Abstract: In one example embodiment of the invention, a simulation based training system is provided having a sensor that unobtrusively collects objective data for individuals and teams experiencing training content to determine the cognitive states of individuals and teams; time-synchronizes the various data streams; automatically determines granular and objective measures for individual cognitive load (CL) of individuals and teams; and automatically determines a cognitive load balance (CLB) and a relative cognitive load (RCL) measure in real or near-real time. Data is unobtrusively gathered through physiological or other activity sensors such as electroencephalogram (EEG) and electrocardiogram (ECG) sensors. Some embodiments are further configured to also include sociometric data in the determining cognitive load. Sociometric data may be obtained through the use of sociometric badges.Type: GrantFiled: September 17, 2020Date of Patent: December 20, 2022Assignee: Aptima, Inc.Inventors: Jeffrey Beaubien, John Feeney, William N. DePriest, Scott Pappada
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Patent number: 11081234Abstract: Embodiments of clinical support systems and methods are disclosed. In one embodiment, methods for clinical performance measurement are disclosed comprising defining a range of acceptable treatment variable values for a treatment variable of a subject, performing a selected intervention, determining an affected treatment variable value and determining a selection performance measure by comparing the affected treatment variable value to the acceptable treatment variable values. In one embodiment, methods for clinical decision training are disclosed comprising defining a treatment variable of a simulated subject, selecting an intervention on the treatment variable, modeling the selected intervention and presenting a visual representation of the selected intervention.Type: GrantFiled: October 3, 2013Date of Patent: August 3, 2021Assignee: Analytic Diabetic Systems, Inc.Inventor: Scott Pappada
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Publication number: 20190313959Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.Type: ApplicationFiled: March 25, 2019Publication date: October 17, 2019Applicant: Aptima, Inc.Inventors: Kevin Durkee, Scott Pappada, Andres Ortiz, William DePriest, John Feeney, Alexandra Geyer, Seamus Sullivan, Sterling Wiggins
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Patent number: 10265008Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.Type: GrantFiled: March 13, 2014Date of Patent: April 23, 2019Assignee: Aptima, Inc.Inventors: Kevin Durkee, Scott Pappada, Andres Ortiz, William DePriest, John Feeney, Alexandra Geyer, Seamus Sullivan, Sterling Wiggins
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Publication number: 20160007899Abstract: Computer based systems and methods for estimating a user state are disclosed. In some embodiments, the methods comprise inputting a first input at an intermittent interval and a second input at a frequent interval into a user state estimation model to estimate the user state. In some embodiments, the first inputs are enhanced by injecting a noise input to create a plurality of enhanced first inputs whereby the plurality of enhance first inputs correspond to the plurality of second inputs at the frequent interval. In some embodiments, the first input comprises a self-reported input and the second inputs comprise a physiological input, a performance input or a situational input. In some embodiments, a machine learning algorithm creates the state estimation model. In some embodiments, the state estimation model estimates a future user state. In some embodiments, a computer based system for estimating a user state is provided.Type: ApplicationFiled: March 13, 2014Publication date: January 14, 2016Applicant: Aptima, Inc.Inventors: Kevin Durkee, Scott Pappada, Andres Ortiz, William DePriest, John Feeney, Alexandra Geyer, Seamus Sullivan, Sterling Wiggins
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Publication number: 20150227710Abstract: Embodiments of clinical support systems and methods are disclosed. In one embodiment, methods for clinical performance measurement are disclosed comprising defining a range of acceptable treatment variable values for a treatment variable of a subject, performing a selected intervention, determining an affected treatment variable value and determining a selection performance measure by comparing the affected treatment variable value to the acceptable treatment variable values. In one embodiment, methods for clinical decision training are disclosed comprising defining a treatment variable of a simulated subject, selecting an intervention on the treatment variable, modeling the selected intervention and presenting a visual representation of the selected intervention.Type: ApplicationFiled: October 3, 2013Publication date: August 13, 2015Applicant: ANALYTIC DIABETIC SYSTEMS, LLCInventor: Scott Pappada
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Publication number: 20080027292Abstract: A computer-implemented method and apparatus assists a user with diabetes management. The apparatus and method enables the user to record a plurality of their life events; record a plurality of their emotions, each corresponding to one of the plurality of life events; record a plurality of their blood glucose levels, each corresponding to one of the plurality of life events; and predict their glucose changes corresponding to their engaging in one of the recorded life events, and having the corresponding emotion to prevent hypoglycemia.Type: ApplicationFiled: October 8, 2007Publication date: January 31, 2008Inventors: Paul Rosman, Scott Pappada
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Publication number: 20070128682Abstract: A predictive technique for treating diabetes mellitus is described whereby a patient's blood glucose levels are monitored “continuously” over an extended period of time and a life-event diary is maintained records all significant life-events (e.g., food intake, medication, exercise, mood/emotions, etc.). This information is analyzed to derive a mathematical model that closely matches the patient's glucose level variations for the period of monitoring. Specific daily time periods of dysglycemic vulnerability are determined by calculating when the mathematical model predicts that crossings of predetermined hyperglycemic and hypoglycemic threshold levels will occur. These predicted periods of vulnerability are then used to devise a therapeutic plan that administers treatment in anticipation of predicted dysglycemic excursions, thereby limiting the extent of those excursions or eliminating them altogether.Type: ApplicationFiled: December 22, 2006Publication date: June 7, 2007Inventors: Paul Rosman, Scott Pappada