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dc.contributor.advisorSasidhar, Kalyan
dc.contributor.authorDhokai, Ronak
dc.date.accessioned2019-03-19T09:31:00Z
dc.date.available2019-03-19T09:31:00Z
dc.date.issued2018
dc.identifier.citationDhokai, Ronak (2018). A Personalized Gait Abnormality Detection System. Dhirubhai Ambani Institute of Information and Communication Technology, v, 28 p. (Acc. No: T00744)
dc.identifier.urihttp://drsr.daiict.ac.in//handle/123456789/778
dc.description.abstractGait refers to walking manner of a person, and it is also an indication of neurologicalhealth status of a person. Gait variability can occur due to factors like aging,injuries and diseases. If not notified or diagnosed at an early stage, this variabilityof gait could lead to lifetime abnormality.In this work, we have proposed a smartphone based solution for the task ofcapturing gait and performing abnormality detection on the sensed data. Usingthe built-in accelerometer, we collected walking data from 10 different users,which consisted of both normal and minor abnormalities. Features such as stridetime and stride length were extracted and the sudden changes in the walk weredetected by calculating the extent of deviation of these features between the walkdata. Individual user based threshold value of deviation was estimated and thedetection algorithm performance was evaluated for each of the 10 users.
dc.publisherDhirubhai Ambani Institute of Information and Communication Technology
dc.subjectAccelerometer Sensor
dc.subjectAlgorithm
dc.subjectPseudo Code
dc.subjectGait
dc.subjectNeurological Health
dc.subjectSmartphone
dc.classification.ddc612.7600285 DHO
dc.titlePersonalized gait abnormality detection system
dc.typeDissertation
dc.degreeM. Tech
dc.student.id201611063
dc.accession.numberT00744


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