Toward autism recognition using hidden Markov models

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dc.contributor.author Lancaster, Joseph Paul Jr.
dc.date.accessioned 2008-05-15T16:06:45Z
dc.date.available 2008-05-15T16:06:45Z
dc.date.issued 2008-05-15T16:06:45Z
dc.identifier.uri http://hdl.handle.net/2097/777
dc.description.abstract The use of hidden Markov models in autism recognition and analysis is investigated. More specifically, we would like to be able to determine a person's level of autism (AS, HFA, MFA, LFA) using hidden Markov models trained on observations taken from a subject's behavior in an experiment. A preliminary model is described that includes the three mental states self-absorbed, attentive, and join-attentive. Futhermore, observations are included that are more or less indicative of each of these states. Two experiments are described, the first on a single subject and the second on two subjects. Data was collected from one individual in the second experiment and observations were prepared for input to hidden Markov models and the resulting hidden Markov models were studied. Several questions subsequently arose and tests, written in Java using the JaHMM hidden Markov model tool- kit, were conducted to learn more about the hidden Markov models being used as autism recognizers and the training algorithms being used to train them. The tests are described along with the corresponding results and implications. Finally, suggestions are made for future work. It turns out that we aren't yet able to produce hidden Markov models that are indicative of a persons level of autism and the problems encountered are discussed and the suggested future work is intended to further investigate the use of hidden Markov models in autism recognition. en
dc.language.iso en_US en
dc.publisher Kansas State University en
dc.subject Hidden Markov model en
dc.subject Autism en
dc.title Toward autism recognition using hidden Markov models en
dc.type Thesis en
dc.description.degree Master of Science en
dc.description.level Masters en
dc.description.department Department of Computing and Information Sciences en
dc.description.advisor David A. Gustafson en
dc.subject.umi Computer Science (0984) en
dc.subject.umi Psychology, Clinical (0622) en
dc.subject.umi Psychology, Developmental (0620) en
dc.date.published 2008 en
dc.date.graduationmonth May en


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