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Sequences of these syllables can be represented by symbols and characterized by a statistical grammar which varies with external situational context and internal neurological state. By first constructing a Markov chain from the transitions between these syllables then calculating the stationary distribution of this chain, we estimate the overall severity of Parkinson\u2019s symptoms by capturing the increasingly disorganized transitions between syllables as motor impairment increases. Comparing stationary distributions of movement syllables has several advantages over traditional neurologist administered in-clinic assessments. This technique can be used on unconstrained at-home behavior as well as scripted in-clinic exercises, it avoids differences across human evaluators, and can be used continuously without requiring scripted tasks be performed. We demonstrate the effectiveness of this technique using movement data captured with commercially available wrist worn sensors in 35 participants with Parkinson\u2019s disease in-clinic and 25 participants monitored at home.<\/jats:p>","DOI":"10.1038\/s41598-020-64181-3","type":"journal-article","created":{"date-parts":[[2020,4,30]],"date-time":"2020-04-30T06:02:59Z","timestamp":1588226579000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Using an unbiased symbolic movement representation to characterize Parkinson\u2019s disease states"],"prefix":"10.1038","volume":"10","author":[{"given":"Avner","family":"Abrami","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Heisig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vesper","family":"Ramos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin C.","family":"Thomas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bryan K.","family":"Ho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vittorio","family":"Caggiano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,4,30]]},"reference":[{"key":"64181_CR1","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1136\/jnnp.2007.131045","volume":"79","author":"J Jankovic","year":"2008","unstructured":"Jankovic, J. 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Abrami, and V. Caggiano describing the method proposed in the manuscript has been filed and published [US Patent App. 16\/001,063]. A. Abrami, S. Heisig, and V. Caggiano disclose that their employer, IBM Research, is the research branch of IBM Corporation. S. Heisig and V. Caggiano own stock in IBM Corporation. V.L. Ramos discloses that her employer, Pfizer Digital Medicine & Translational Imaging: Early Clinical Development, is a research branch of Pfizer Corporation. V. Ramos owns stock in Pfizer Corporation. B.K. Ho is employed by the Department of Neurology, Tufts University School of Medicine and Tufts Medical Center. K. Thomas is employed by the Spivack Center for Clinical and Translational Neuroscience, Boston University School of Medicine.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"7377"}}