Autonomous Data Collection is as Effective as Laboratory-Based Data Collection Using a Joint Position Sense Application

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dc.contributor.authorMankala, Vikas Medhansh
dc.date.accessioned2017-10-12T14:35:46Z
dc.date.available2017-10-12T14:35:46Z
dc.date.issued2017
dc.description35 pages. A thesis presented to the Department of Human Physiology and the Clark Honors College of the University of Oregon in partial fulfillment of the requirements for degree of Bachelor of Science, Spring 2017
dc.description.abstractProprioception is the unconscious awareness of body position and motion in space that enables the freedom of daily physical tasks. A submodality of proprioception, joint position sense, is an important clinical metric that has previously been assessed in both passive and active protocols. Recently, our laboratory has shown that joint position sense assessed using an active repositioning task can accurately be measured using a smartphone application. However, a visit to a laboratory is still required, which can be time-intensive and expensive. The objective of this study was to demonstrate that autonomous measurement using a joint position sense application is as consistent and reliable as laboratory-based measurement. We recruited 20 healthy subjects from the University of Oregon. Our results demonstrated no main effect of condition, and similar patterns to what has been measured in the past - repositioning errors decrease with increasing shoulder flexion angles. These results show promise for future protocols to implement autonomous measurement when assessing joint position sense.en_US
dc.identifier.urihttps://hdl.handle.net/1794/22868
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsCreative Commons BY-NC-ND 4.0-US
dc.subjectAutonomous measurementen_US
dc.subjectData collectionen_US
dc.subjectJoint positionen_US
dc.subjectMobile applicationsen_US
dc.subjectProprioceptionen_US
dc.subjectShoulder Flexionen_US
dc.titleAutonomous Data Collection is as Effective as Laboratory-Based Data Collection Using a Joint Position Sense Application
dc.typeThesis/Dissertation

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