Can Technology Make a Difference in Pediatric Rehabilitation? – A NCMRR Webcast

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Interested in how technology can be used to make a difference in pediatric rehabilitation? A video cast from the National Center for Medical Rehabilitation Research (NCMRR) discusses the topic in Bethesda MD. The workshop is organized by the Motion Analysis Laboratory and supported by the National Science Foundation and the National Institutes of Health.

The workshop on August 9th, 2016 brought together a group of experts in rehabilitation to discuss how technology can help us to address pressing needs in pediatric rehabilitation. To follow all of the talks this past week and listen to “Can Technology Make a Difference in Pediatric Rehabilitation?”, follow this link, CLICK HERE.

J Wu, BR Shuman, BW Brunton, KM Steele, JD Olson, RPN Rao (2016) “Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features.” IEEE Engineering Medicine & Biology

Dr. Steele JournalArticle, MotorControl ,
J Wu, BR Shuman, BW Brunton, KM Steele, JD Olson, RPN Rao (2016) “Multistep model for predicting upper-limb 3D isometric force application from pre-movement electrocorticographic features.” IEEE Engineering Medicine & Biology

Peer-reviewed paper at IEEE Engineering in Medicine & Biology Annual Conference:

Can we estimate upper-extremity force production from electrocorticographic recordings?

Example of ECoG recording during upper-extremity force production.Abstract: Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals. We also find direction-distinguishing information up to 400ms before force onset in the pre-movement signals, captured by electrodes placed over the limb-ipsilateral dorsal premotor regions. This approach can contribute to more accurate decoding of higher-level movement goals, at earlier timescales, and inform sensor placement. Our results also contribute to further understanding of the spatiotemporal features of human motor planning.

Perfect Pitch Competition – Gaurav places after presenting his research in 90 seconds

Keshia News

Gaurav Mukherjee participated and won the second position among the UWIN Fellows at the Perfect Pitch competition organized by the Washington Research Foundation funded institutes on Tuesday July 12, 2016

The Perfect Pitch Contest is an opportunity to develop the communication skills needed to explain your research question, the solution you are developing, and the potential impact of the project in a clear, concise, and compelling fashion.  This skill is essential for any career path including academia, industry, and government.  A smart pitch could help you get a job, win funding for a grant, persuade a collaborator to partner with you, or perhaps even fund your startup company.

The Perfect Pitch contest provides participants the opportunity to present a 90-second pitch and one slide related to their research.

Recent UWIN Awardees stand in a line in front of their posters. Gaurav Mukherjee gives his 90 second research pitch to an auditorium filled with people.