6852 Caprice Ave, Baton Rouge, LA 70811 • (225)3571315
Somerville, TN
Work
Company:
Department of biomedical engineering, case western reserve university
Aug 2006
Position:
Graduate research assistant
Education
School / High School:
Case Western Reserve University- Cleveland, OH
Jan 2010
Specialities:
Ph.D. in Biomedical Engineering
Skills
Preparing IRB protocols and FDA IDE subm... • statistical analysis • pattern recognition • real-time control algorithm prototyping • digital signal processing • data mining • and physiological system identification ... • R • LabView • NEURON
Machine Learning Statistics Pattern Recognition Signal Processing System Identification Biomedical Engineering Neural Networks Matlab Algorithms Medical Devices Mathematical Modeling Experimental Design Simulink Biomechanics Minitab Research Data Analysis R R&D Clinical Research
Department of Biomedical Engineering, Case Western Reserve University
Aug 2006 to 2000 Graduate Research AssistantBoston Scientific Minneapolis, MN May 2011 to Aug 2011 Device Innovations InternLouis Stokes Cleveland VA Medical Center Cleveland, OH May 2005 to May 2006 Research AssistantSummer Program in Undergraduate Research, Case Western Reserve University Cleveland, OH May 2004 to Jul 2004 Summer Research Assistant
Education:
Case Western Reserve University Cleveland, OH Jan 2010 to Jan 2012 Ph.D. in Biomedical EngineeringCase Western Reserve University Cleveland, OH Jan 2006 to Jan 2010 M.S. in Biomedical EngineeringCase Western Reserve University Cleveland, OH Jan 2002 to Jan 2006 B.S.E. in Biomedical Engineering
Skills:
Preparing IRB protocols and FDA IDE submissions Expertise in time series prediction, statistical analysis, pattern recognition, real-time control algorithm prototyping, digital signal processing, data mining, and physiological system identification Extensive MATLAB/Simulink/xPC Target - Proficient in C/C++, R, LabView, NEURON
Us Patents
Movement Disorder Therapy System, Devices And Methods, And Intelligent Methods Of Tuning
Dustin A Heldman - Shaker Heights OH, US Christopher L Pulliam - Shaker Heights OH, US Joseph P Giuffrida - Hinckley OH, US Thomas O Mera - South Euclid OH, US
International Classification:
A61N 1/372
US Classification:
607 45
Abstract:
The present invention relates to methods for tuning treatment parameters in movement disorder therapy systems. The present invention further relates to a system for screening patients to determine viability as candidates for certain therapy modalities, such as deep brain stimulation (DBS). The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson's disease and Parkinsonism, Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of tuning a therapy device using objective quantified movement disorder symptom data acquired by a movement disorder diagnostic device to determine the therapy setting or parameters to be provided to the subject via his or her therapy device. The present invention also provides treatment and tuning remotely, allowing for home monitoring of subjects.
Movement Disorder Therapy System And Methods Of Tuning Remotely, Intelligently And/Or Automatically
Dustin A. Heldman - Shaker Heights OH, US Christopher L. Pulliam - Shaker Heights OH, US Joseph P. Giuffrida - Hinckley OH, US Thomas O. Mera - South Euclid OH, US
International Classification:
A61N 1/372 A61N 1/36
US Classification:
607 45
Abstract:
The present invention relates to methods for remotely and intelligently tuning movement disorder of therapy systems. The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson's disease and Parkinsonism, Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of remotely and intelligently or automatically tuning a therapy device using objective quantified movement disorder symptom data to determine the therapy setting or parameters to be transmitted and provided to the subject via his or her therapy device. The present invention also provides treatment and tuning intelligently, automatically and remotely, allowing for home monitoring of subjects.
Method And Apparatus For Automatic Arrhythmia Classification With Confidence Estimation
Christopher Pulliam - South Euclid OH, US Yanting Dong - Lexington KY, US David L. Perschbacher - Coon Rapids MN, US
Assignee:
Cardiac Pacemakers, Inc. - St. Paul MN
International Classification:
A61B 5/04 A61B 5/0464
US Classification:
600518, 600515
Abstract:
An arrhythmia classification system receives cardiac data from an implantable medical device, performs automatic adjudication of each cardiac arrhythmia episode indicated by the cardiac data, and generates episode data representative of information associated with the episode. The episode data include at least an episode classification resulting from the automatic adjudication of the episode and a confidence level in the episode classification. In one embodiment, the episode data further include key features rationalizing the automatic adjudication of the episode.
Implantable Medical Leads Having Electrode Segments Of Different Sizes
- Minneapolis MN, US Michelle A. Case - Blaine MN, US Paula A. Dassbach - Minneapolis MN, US Abbey B.H. Becker - Shoreview MN, US Christopher L. Pulliam - Plymouth MN, US
International Classification:
A61N 1/04 A61N 1/05
Abstract:
Implantable medical leads include rows of electrode segments where electrode segments within a given row may be a different size and/or adjacent electrode segments of adjacent rows may be of a different size. The arrangement of the electrode segments of different sizes may avoid intersections of the spaces between segments to reduce the size and/or number of blind spots that otherwise occur for delivery of stimulation signals and/or sensing of physiological signals. The electrode segments of different sizes may be of a same shape type but with different proportions.
- Minneapolis MN, US Steven M. Goetz - North Oaks MN, US Christopher L. Pulliam - Plymouth MN, US Scott R. Stanslaski - Shoreview MN, US
International Classification:
A61N 1/36 A61N 1/372
Abstract:
A method for assessment of brain signals of a patient includes determining, by one or more processors, a cluster of neural data occurring at a brain of the patient and outputting, by the one or more processors, a request for a user to provide patient state information for the cluster of the neural data in response to determining that the cluster of the neural data is occurring at the brain of the patient. The method further includes associating, by the one or more processors, the patient state information with the cluster of the neural data to generate patient assessment information and outputting, by the one or more processors, the patient assessment information.
- Minneapolis MN, US David E. Linde - Corcoran MN, US Scott R. Stanslaski - Shoreview MN, US Christopher L. Pulliam - Plymouth MN, US Rene A. Molina - Maple Grove MN, US Abbey Beuning Holt Becker - Shoreview MN, US David L. Carlson - Fridley MN, US Nicholas D. Buse - New Brighton MN, US Duane L. Bourget - Andover MN, US Thaddeus S. Brink - St. Paul MN, US
International Classification:
A61N 1/36 A61N 1/05 A61N 1/372
Abstract:
An example method includes determining, by an implantable medical device (IMD), an electrode of a plurality of electrodes of a lead to be used to deliver electrical stimulation to a patient at a particular time; selecting, by the IMD and based on the determined electrode, a set of electrodes of the plurality of electrodes; and sensing, by the IMD and via the selected set of electrodes, electrical signals of the patient at the particular time.
- Minneapolis MN, US Robert S. Raike - Minneapolis MN, US Benjamin P. Isaacson - Mahtomedi MN, US Christopher L. Pulliam - Plymouth MN, US Abbey Beuning Holt Becker - Shoreview MN, US Michelle A. Case - Blaine MN, US
International Classification:
A61N 1/36 A61N 1/02
Abstract:
A medical device for providing electrical stimulation to a brain of a patient includes one or more processors. The one or more processors are configured to determine a first set of parameters of a first electrical signal that is delivered via a first electrode configured to apply electrical stimulation to a first region of the brain and to determine a second set of parameters of a second electrical signal based on the first set of parameters. The second electrical signal is delivered via a second electrode configured to apply electrical stimulation to a second region of the brain. The one or more processors are further configured to deliver, with the first electrode, the first electrical signal having the first set of parameters and to deliver, with the second electrode, the second electrical signal having the second set of parameters.
- Minneapolis MN, US Rene A. Molina - Maple Grove MN, US Christopher L. Pulliam - Plymouth MN, US
International Classification:
A61N 1/36 A61N 1/372 A61N 1/05
Abstract:
Devices, systems, and techniques are disclosed for managing electrical stimulation therapy and/or sensing of physiological signals such as brain signals. For example, a system is configured to receive, for each electrode combination of a plurality of electrode combinations, information representing a signal sensed in response to first electrical stimulation delivered to a patient via a lead, wherein the plurality of electrode combinations comprise different electrode combinations comprising electrode disposed at different positions around a perimeter of the lead implanted in the patient. The system may also be configured to determine, based on the information for each electrode combination of the plurality of electrode combinations, values for a threshold at different locations around the perimeter of the lead and determine, based on the values for the threshold, one or more stimulation parameter values that at least partially define second electrical stimulation deliverable to the patient via the lead.
Southeast Guilford High School Greensboro NC 1982-1986
Community:
Bonnie Morris, David Andrews, Eddie Carrico, Traci Bowman, Susan Henley, Gregory Ayers, Craig Herndon, Stephen Marley, Kimberly May, Nicki Ritchie, Michael Shuff
Southeast Guilford High School Greensboro NC 1983-1987
Community:
Bonnie Morris, Eddie Carrico, Traci Bowman, Susan Henley, Gregory Ayers, Stephanie Creed, Stephen Marley, Krishna Hooker, Kimberly May, Dennis Brouwer, Nicki Ritchie