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Vibrotactile Sensory Augmentation and Machine Learning Based Approaches for Balance Rehabilitation

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서명/저자사항Vibrotactile Sensory Augmentation and Machine Learning Based Approaches for Balance Rehabilitation.
개인저자Bao, Tian.
단체저자명University of Michigan. Mechanical Engineering.
발행사항[S.l.]: University of Michigan., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항215 p.
기본자료 저록Dissertation Abstracts International 79-12B(E).
Dissertation Abstract International
ISBN9780438127203
학위논문주기Thesis (Ph.D.)--University of Michigan, 2018.
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Kathleen Helen Sienko.
요약Vestibular disorders and aging can negatively impact balance performance. Currently, the most effective approach for improving balance is exercise-based balance rehabilitation. Despite its effectiveness, balance rehabilitation does not always re
요약Vibrotactile SA provides a form of haptic cues to complement and/or replace sensory information from the somatosensory, visual and vestibular sensory systems. Previous studies have shown that people can reduce their body sway when vibrotactile S
요약In addition to investigating the effects of long-term balance training with SA, we sought to study the effects of vibrotactile display design on people's reaction times to vibrational cues. Among the various factors tested, the vibration frequen
요약Lastly, we explored the potential for ML to inform balance exercise progression for future applications of unsupervised balance training. We mapped body motion data measured by wearable inertial measurement units to balance assessment ratings pr
요약The findings of this dissertation suggest that vibrotactile SA can be used as a rehabilitation tool to further improve a subset of clinical outcomes resulting from supervised balance rehabilitation training. Specifically, individuals who train w
일반주제명Mechanical engineering.
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