Arizona State University
Biomedical Capstone Teaching Assitant
Medtronic May 2017 - Aug 2017
Graduate Engineer Intern
Medtronic May 2017 - Aug 2017
Contingent System Engineer
Arizona State University May 2017 - Aug 2017
Research Assistant
Arizona State University Jan 2013 - Jul 2014
Lab Technician
Education:
Arizona State University 2012 - 2016
Skills:
Microsoft Office Microsoft Excel Data Analysis Powerpoint Matlab Microsoft Word Public Speaking Labview Impedance Spectroscopy Design of Experiments Solidworks Mixed Signal Sensors Leadership Electrochemistry Statistics Impedance Analyzer Research Biochemistry Electrochemical Characterization C++ Team Management
- Minneapolis MN, US Michael D. Eggen - Chisago City MN, US Ning Yu - Columbia Heights MN, US John P. Keane - Shoreview MN, US Shantanu Sarkar - Roseville MN, US Randal C. Schulhauser - Phoenix AZ, US David L. Probst - Chandler AZ, US Mark R. Boone - Gilbert AZ, US Kenneth A. Timmerman - Robbinsdale MN, US Stanley J. Taraszewski - Plymouth MN, US Matthew A. Joyce - Maple Grove MN, US Amruta Paritosh Dixit - Maple Grove MN, US Kathryn E. Hilpisch - Cottage Grove MN, US Kathryn Ann Milbrandt - Ham Lake MN, US Laura M. Zimmerman - Maple Grove MN, US Matthew L. Plante - Danbury WI, US
This disclosure is directed to systems and techniques for detecting change in patient health based upon patient data. In one example, a medical system comprising processing circuitry communicably coupled to a glucose sensor and configured to generate continuous glucose sensor measurements of a patient. The processing circuitry is further configured to: extract at least one feature from the continuous glucose sensor measurements over at least one time period, wherein the at least one feature comprises one or more of an amount of time within a pre-determined glucose level range, a number of hypoglycemia events, a number of hyperglycemia events, or one or more statistical metrics corresponding to the continuous glucose sensor measurements; apply a machine learning model to the at least one extracted feature to produce data indicative of a risk of a cardiovascular event; and generate output data based on the risk of the cardiovascular event.
Detection And/Or Prediction Of A Medical Condition Using Atrial Fibrillation And Glucose Measurements
- Mansfield MA, US David L. Probst - Chandler AZ, US Mohsen Askarinya - Chandler AZ, US Aaron Gilletti - Costa Mesa CA, US Richard J. O'Brien - Hugo MN, US Mark J. Phelps - Scottsdale AZ, US Randal C. Schulhauser - Phoenix AZ, US John Wainwright - Foothill Ranch CA, US
A system comprises electrocardiogram sensing, glucose sensing circuitry, and processing circuitry. The sensing circuitry is configured to sense an electrocardiogram of a patient. The glucose sensing circuitry is configured to sense glucose levels of the patient. The processing circuitry configured to detect atrial fibrillation of the patient during a time unit based on the electrocardiogram of the patient, determine a first metric, wherein the first metric is associated with atrial fibrillation the patient experiences during the time unit, determine a second metric, wherein the second metric is associated with glucose levels of the patient during the time unit, and generate a health metric, wherein the health metric is determined based on the first and second metrics.
Jeffrey LaBelle - Tempe AZ, US David Probst - Tempe AZ, US Bin Mu - Tempe AZ, US
International Classification:
A61B 5/1486 A61B 5/145 A61B 5/1473
Abstract:
Embodiments of the present disclosure relate generally devices for detecting analytes in a subject. More particularly, the present disclosure provides a biosensor array for detecting analytes in a subject. Embodiments of the present disclosure include a biosensor array comprising a plurality of sensor cells for detecting an analyte in a subject. In accordance with these embodiments, the plurality of sensor cells comprises at least one electrode, at least one antibody immobilized on a surface of the at least one electrode, and a biodegradable coating in contact with the at least one antibody.
Waferscale Physiological Characteristic Sensor Package With Integrated Wireless Transmitter
- Northridge CA, US David L. Probst - Chandler AZ, US Randal C. Schulhauser - Phoenix AZ, US Mohsen Askarinya - Chandler AZ, US Patrick W. Kinzie - Glendale AZ, US Thomas P. Miltich - Otsego MN, US Mark D. Breyen - Champlin MN, US
An embodiment of a sensor device includes a base substrate, a circuit pattern formed overlying the interior surface of the substrate, a physiological characteristic sensor element on the exterior surface of the substrate, conductive plug elements located in vias formed through the substrate, each conductive plug element having one end coupled to a sensor electrode, and having another end coupled to the circuit pattern, a multilayer component stack carried on the substrate and connected to the circuit pattern, the stack including features and components to provide processing and wireless communication functionality for sensor data obtained in association with operation of the sensor device, and an enclosure structure coupled to the substrate to enclose the interior surface of the substrate, the circuit pattern, and the stack.
Dry Electrochemical Impedance Spectroscopy Metrology For Conductive Chemical Layers
- Northridge CA, US Akhil Srinivasan - Woodland Hills CA, US David L. Probst - Chandler AZ, US Melissa Tsang - Los Angeles CA, US Mohsen Askarinya - Chandler AZ, US Riley Clayton Kimball - Tempe AZ, US Robert McKinlay - West Hills CA, US Vu Nguyen - Chandler AZ, US Wally Dong - Chandler AZ, US Xin Heng - Glendale CA, US Brennan Toshner - Northridge CA, US
Assignee:
Medtronic MiniMed, Inc. - Northridge CA
International Classification:
A61B 5/1468 A61B 5/145
Abstract:
A method of testing one or more analyte sensors each comprising a first electrode; a second electrode; and a material layer disposed on or above the first electrode; the method including (a) applying a voltage potential to the first electrode with respect to the second electrode; (b) measuring a test signal comprising an output current from the first electrode that results from the application of the voltage potential; (c) using the test signal from (b) to observe an electrical characteristic of the analyte sensor; and (d) correlating the electrical characteristic a parameter associated with an electrochemical response of the analyte sensor to an analyte, wherein the testing is under dry conditions without exposure of the electrodes to a fluid containing the analyte or an in-vivo environment containing the analyte.
Waferscale Physiological Characteristic Sensor Package With Integrated Wireless Transmitter
- Northridge CA, US David L. Probst - Chandler AZ, US Randal C. Schulhauser - Phoenix AZ, US Mohsen Askarinya - Chandler AZ, US Patrick W. Kinzie - Glendale AZ, US Thomas P. Miltich - Otsego MN, US Mark D. Breyen - Champlin MN, US
An embodiment of a sensor device includes a base substrate, a circuit pattern formed overlying the interior surface of the substrate, a physiological characteristic sensor element on the exterior surface of the substrate, conductive plug elements located in vias formed through the substrate, each conductive plug element having one end coupled to a sensor electrode, and having another end coupled to the circuit pattern, a multilayer component stack carried on the substrate and connected to the circuit pattern, the stack including features and components to provide processing and wireless communication functionality for sensor data obtained in association with operation of the sensor device, and an enclosure structure coupled to the substrate to enclose the interior surface of the substrate, the circuit pattern, and the stack.
- Northridge CA, US Peter Ajemba - Canyon Country CA, US Steven C. Jacks - Culver City CA, US Robert C. Mucic - Glendale CA, US Tyler R. Wong - Pasadena CA, US Melissa Tsang - Sherman Oaks CA, US Chi-En Lin - Van Nuys CA, US Mohsen Askarinya - Chandler AZ, US David Probst - Chandler AZ, US
International Classification:
A61M 5/172 A61B 5/145 A61M 5/142 A61B 5/1495
Abstract:
Medical devices and related systems and methods are provided. A method of calibrating an instance of a sensing element involves obtaining fabrication process measurement data from a substrate having the instance of the sensing element fabricated thereon, obtaining a calibration model associated with the sensing element, determining calibration data associated with the instance of the sensing element for converting the electrical signals into a calibrated measurement parameter based on the fabrication process measurement data using the calibration model, and storing the calibration data in a data storage element associated with the instance of the sensing element.
Apparatus And Methods For Detection Of Diabetes-Associated Molecules Using Electrochemical Impedance Spectroscopy
- Scottsdale AZ, US - Rochester MN, US David Probst - Chandler AZ, US Koji Sode - Chapel Hill NC, US Curtiss Cook - Scottsdale AZ, US
International Classification:
G01N 27/02 G01N 27/327 G01N 33/543
Abstract:
Methods and apparatus for detecting binding of a diabetes-related target molecule analyte in a sample utilizing Electrochemical Impedance Spectroscopy (EIS). Sensor electrodes include a diabetes-related target-capturing molecule immobilized thereto, and an EIS-based imaginary impedance measurement is utilized to arrive at a concentration of the analyte.