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PROFILE:

 

Anusha Venkatakrishnan

Anusha Venkatakrishnan is a clinical neuroscientist within the Interactive Intelligence team. Currently, she is working on translating mobile technology-based, behavioral change interventions developed at PARC for relevant clinical applications. She also collaborates with other teams in development of novel therapeutic devices and interventions for neurological disorders. 

Prior to joining PARC, Anusha was a clinical scientist at the Texas Medical Center in Houston, where she was the lead liaison between the Electrical & Computer Engineering laboratory at the University of Houston and clinical partners at the medical center. During her time there, she started up and managed some of the first-in-human clinical trials involving applications of brain-computer interfaces and rehabilitation robotic devices for patients with stroke and spinal cord injuries. Before that, Anusha was a scientific reviewer for ClinicalTrials.gov at the National Institutes of Health (NIH). She has reviewed over 2000 clinical trials while at NIH, and consulted with and advised the biopharmaceutical industry on FDA compliant reporting of clinical trial design and results. She has a lot of experience in federal regulations pertinent to clinical trial conduct. 

Dr. Venkatakrishnan earned her Ph.D. in Neuroscience and Cognitive Sciences and M.A. in Kinesiology from the University of Maryland, College Park. As a predoctoral fellow at the NIH, she investigated clinical effects of noninvasive brain stimulation through interdisciplinary research spanning neuroimaging, signal processing, statistical modeling and human behavioral experiments. For this work, she received a Fellows Award for Research Excellence competing with postdoctoral researchers across all institutes at the NIH. She is also a licensed physical therapist and received her Bachelors degree in Physical therapy (summa cum laude) from Seth G.S. Medical College & K.E.M. Hospital at Mumbai, India.

 

 

 

other publications

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2017

On Designing a Social Coach to Promote Regular Aerobic Exercise

Proceedings of the 29th Annual Conference on Innovative Applications of Artificial Intelligence/AAAI

2016

Acceptability of a team-based mobile health (mHealth) application for lifestyle self-management in individuals with chronic illnesses

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS)

Rehabilitation Technologies for Spinal Injury

Emerging Therapies in Neurorehabilitation II: Chapter 3

2016

A Group-Based Mobile Application to Increase Adherence in Exercise and Nutrition Programs: A Factorial Design Feasibility Study

Journal of Medical & Internet Research mHealth and uHealth

2016

2015

The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study

Journal of Neuroengineering and Rehabilitation

2015

Real-Time Strap Pressure Sensor System for Powered Exoskeletons

Sensors: Physical Sensors

2015

2014

Detecting Movement Intent from Scalp EEG in a Novel Upper Limb Robotic Rehabilitation System for Stroke

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS)

2014

An integrated neuro-robotic interface for stroke rehabilitation using the NASA X1 powered lower limb exoskeleton.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS)

2014

Applications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation.

Current Physical Medicine and Rehabilitation reports

2014

2012

Combining transcranial direct current stimulation and neuroimaging: novel insights in understanding neuroplasticity

Journal of Neurophysiology

2012

2011

Independent component analysis of resting brain activity reveals transient modulation of local cortical processing by transcranial direct current stimulation

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS)

2011

Parkinson's disease differentially affects adaptation to gradual as compared to sudden visuomotor distortions

Human Movement Science

2011