Location

Phoenix, Arizona

Contact

Pradhan.Gaurav@mayo.edu

SUMMARY

The research interests of Gaurav N. Pradhan, Ph.D., focus on data mining, pattern recognition, knowledge discovery, machine learning, cluster analysis, association rule mining and content-based similarity retrieval in the context of high-dimensional, multisensor and multistream databases. Dr. Pradhan is specifically interested in developing real-time computational and mathematical models and simulations in medicine, conducting health care data analytics and mining, and creating data visualizations in biomedical informatics.

Dr. Pradhan's research primarily includes developing novel, real-time, eye-tracking technology as a biomarker of cognitive impairment. He is also actively working on the development of real-time computational models to generate multiaxial galvanic vestibular commands matching motions in the visual scene particularly in the areas of flight simulations, medical applications and entertainment.

Focus areas

  • Eye tracking and cognitive performance. Dr. Pradhan is investigating the development of a real-time computational model with the software (nonexclusively licensed) to compute multiple, complex oculometric performance measurements from any noninvasive eye-tracking technology that can be used to derive subtle changes in cognitive performance. Current focus is on detecting decrement in cognitive performance due to the influence of acute hypoxia and hyperventilation in the field of aerospace medicine. Another focus area is on diagnosing concussion and monitoring its recovery in the field of neurology.
  • Real-time galvanic vestibular stimulation (GVS). Dr. Pradhan is investigating the development of licensed mathematical pattern recognition algorithms for matching GVS to motion in any visual scenes (movies, games) in real time. The focus is to incredibly enhance the sophistication and fidelity of experiencing motion happening in the visual scenes, and to also significantly mitigate motion, simulator or virtual reality sickness.
  • Diagnostic visualization tool. Dr. Pradhan is investigating the development of a patented, multidimensional data visualization tool that displays complex multidimensional data and enables users to interactively discover multivariate relationships among a large number of dimensions of data. The focus of this tool is to provide simplified diagnostic views, allowing users to quickly compare and visualize individual multidimensional data points with normative samples.
  • Objective quantification of simulator sickness. Dr. Pradhan is investigating the development of data analytic and mining technique to analyze continuous electrogastrography (EGG) signals to quantify motion or simulator sickness that causes vestibulo-autonomic responses to increase sympathetic activity and decrease parasympathetic activity.
  • Analyzing body composition (BOD POD). Development of graphical visual analytic software on more than 10,000 BOD POD data samples and radial tonometry data samples. The focus is to find significant patterns, correlations and associations to identify relationships between different medical conditions, body composition, and central and peripheral hemodynamic parameters.
  • Quantification of antigravity (anti-G) straining maneuver. Implementation of a patented algorithm to quantify anti-G straining maneuver (AGSM) by measuring the resistance of the peripheral vasculature through calculating the augmentation index from a blood pressure wave in any associated body parts such as the finger, thumb, arm, abdomen or foot. The AGSM is the important part of acceleration protection against gravity-induced loss of consciousness. Proper AGSM serves to increase the resistance of the peripheral vasculature so that blood will preferentially flow in the brain.

Significance to patient care

Dr. Pradhan has transformed the GVS technique by synchronizing it with the visual field through the development of a proprietary algorithm for identifying 3-D movement information in yaw, pitch and roll directions during visual simulation, then providing corresponding multiaxial GVS commands in real time. This technology has potential applications not only for providing quantitative diagnostic tools for various balance disorders and vertigo, but also to facilitate rehabilitative tools for balance retraining.

Dr. Pradhan's work on studying oculometrics and finding patterns for cognitive impairment in eye movements will assist in advancing the clinical assessment of neurological disorders such as early diagnosis of dementias and concussions, and detection of central nervous system impairment due to prescribed drugs. Additionally, this technology can also assist in the detection of dangerous microsleep and the influence of alcohol or drugs.

Professional highlights

  • Advisory council member, Committee on Credible Practice of Modeling and Simulation in Healthcare, 2016-2017
  • Consultant, Safety and Mission Assurance Program to review Integrated Medical Model to forecast risk of crew health and space mission success, NASA, 2015-2016
  • Workshop chair, International Conference on Healthcare Informatics, Institute of Electrical and Electronics Engineers, 2015
  • Recipient, Arnold D. Tuttle Award, Aerospace Medical Association for the most important journal article in aerospace medicine, 2013

PUBLICATIONS

See my publications

PROFESSIONAL DETAILS

Academic Rank

  1. Assistant Professor of Biomedical Informatics

EDUCATION

  1. PhD - Computer Science Dissertation Title: On Analyzing Multiple, Physiological Sensor Databases The dissertation focuses on performing efficient clustering analysis and content-based similarity retrieval, indexing for faster retrieval, mining of association rules containing frequent events of patterns, and effective performance analysis with visualization that can provide proper interpretation in an integrated environment of multiple, multidimensional physiological sensor databases. University of Texas at Dallas
  2. MS - Computer Science (Research Track) Thesis Title: Indexing and Compression of Multi-Attribute, Variable Length, Multidimensional Motion Data University of Texas at Dallas
  3. BE - Computer Engineering University of Mumbai
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BIO-20207526

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