Deborah S. Won
California State University, Los Angeles
35 Papers
119 Citations
Deborah S. Won is an academic researcher from California State University, Los Angeles. The author has contributed to research in topics: Medicine & Spinal cord injury. The author has an hindex of 8, co-authored 31 publications. Previous affiliations of Deborah S. Won include Duke University & California State University.
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Papers
Implementing Collaborative Project-Based Learning using the Tablet PC to enhance student learning in engineering and computer science courses
Zanj Avery,Mauricio Castillo,Huiping Guo,Jiang Guo,Nancy Warter-Perez,Deborah S. Won,Jane Dong +6 more
- 23 Dec 2010
TL;DR: A team effort to implement Collaborative Project-based Learning using Tablet PC technology in a broad spectrum of engineering and computer science courses from freshman to senior level to address the challenges for minority students is presented.
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Deep Brain Stimulation: An Evolving Technology
M.A. Liker,Deborah S. Won,V.Y. Rao,S.E. Hua +3 more
- 17 Jun 2008
TL;DR: Some of the engineering advances that will enable DBS to yield a more predictable outcome for current indications and to be systematically developed as a treatment for new indications are pointed toward.
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An EMG-based system for continuous monitoring of clinical efficacy of Parkinson's disease treatments
Sina Askari,Mo Zhang,Deborah S. Won +2 more
- 11 Nov 2010
TL;DR: This system was designed to provide continuous measures of tremor, rigidity, and bradykinesia which are related to the neurophysiological source without the need for multiple bulky experimental apparatuses, thus allowing more precise, quantitative indicators of the symptoms which can be measured during practical daily living tasks.
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Robotic assistance that encourages the generation of stepping rather than fully assisting movements is best for learning to step in spinally contused rats.
TL;DR: The findings suggested that flexible robotic assistance facilitated learning to step after a SCI, and support the rationale for the use of AAN robotic training algorithms in human robotic-assisted BWSTT.
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A simulation study of information transmission by multi-unit microelectrode recordings.
Deborah S. Won,Patrick D. Wolf +1 more
TL;DR: To analyse the information content of multi-unit signals, cases of two and three superimposed neural responses to a stimulus were simulated and it was found that information in single-unit responses is not completely lost when multiple units are superimposed.
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