Augmented biofeedback for partial weight-bearing learning

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dc.contributor.advisorBateman, Scott
dc.contributor.advisorScheme, Erik
dc.contributor.authorSmith, Ian
dc.date.accessioned2023-03-01T16:20:41Z
dc.date.available2023-03-01T16:20:41Z
dc.date.issued2019
dc.date.updated2022-04-05T00:00:00Z
dc.description.abstractAssistive devices, including canes and crutches, are used in partial weight-bearing (PWB)–offloading weight from limbs weakened by disease or injury to promote recovery and prevent reinjury. While it is important to accurately offload weight to target loads prescribed by healthcare providers, current training methods result in poor compliance. It is currently unknown how to most effectively provide feedback during training to allow users accurate execution of the skill later on. In this work, three studies were conducted to investigate the effects of feedback modality, delay, and resolution on both regulation and learning of PWB while stationary and during gait. Results indicate that concurrent feedback is best suited for continuous skill regulation whereas retrospective feedback is preferable for training PWB, and that task-specific training is critical for compliance. This work presents design guidelines for improved clinical PWB training methods and highlights the importance of researching retrospective motor learning methods.
dc.description.copyright© Ian Smith, 2019
dc.formattext/xml
dc.format.extentxiv, 109 pages
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/13583
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.titleAugmented biofeedback for partial weight-bearing learning
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.fullnameMaster of Computer Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.C.S.

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