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Diagnostic Analysis of Postural Data using Topological Data Analysis

Abstract Details

2019, Master of Science, Miami University, Mechanical and Manufacturing Engineering.
Understanding the mechanisms behind human balance has been a prominent subject of interest as various postural instabilities have been linked to neuromuscular impairments and diseases (Parkinson's, multiple sclerosis, and concussions). This thesis presents an unsupervised method that breaks any physical model, given a sampled manifold, into its local system behaviors, and allows for the detection of intermittent instabilities in an individual’s postural stance via a co-activation topological mapping scheme. The proposed co-activation topological mapping scheme is extremely powerful because it not only allows for a diagnostic analysis of an individual's postural stance through locating the mechanisms responsible for their intermittent instabilities, but for subjects who are not exhibiting intermittent instabilities. This topological mapping method is able to differentiate between stable individual's postural data.
James Chagdes, Dr (Advisor)
Shukla Amit, Dr (Committee Member)
Kramer Ryan, Dr (Committee Member)
54 p.

Recommended Citations

Citations

  • Siegrist, K. W. (2019). Diagnostic Analysis of Postural Data using Topological Data Analysis [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1564748543676698

    APA Style (7th edition)

  • Siegrist, Kyle. Diagnostic Analysis of Postural Data using Topological Data Analysis. 2019. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1564748543676698.

    MLA Style (8th edition)

  • Siegrist, Kyle. "Diagnostic Analysis of Postural Data using Topological Data Analysis." Master's thesis, Miami University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=miami1564748543676698

    Chicago Manual of Style (17th edition)