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The purpose of this thesis is to determine whether Tai Chi Qigong or Health Information podcasts are more effective for improving mental health and sleep outcomes for midlife women with mobility impairments. No other studies have been done to investigate whether Tai Chi can be more effective for sleep, depressive symptoms, and anxiety for midlife women with mobility impairments specifically. Overall, it was found that midlife women with mobility impairments experienced better sleep when they focused on health information podcasts in comparison to Tai Chi. Change in anxiety and depressive symptoms were negligible.
The purpose of this thesis is to determine whether Tai Chi Qigong or Health Information podcasts are more effective for improving mental health and sleep outcomes for midlife women with mobility impairments. No other studies have been done to investigate whether Tai Chi can be more effective for sleep, depressive symptoms, and anxiety for midlife women with mobility impairments specifically. Overall, it was found that midlife women with mobility impairments experienced better sleep when they focused on health information podcasts in comparison to Tai Chi. Change in anxiety and depressive symptoms were negligible.
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The importance of nonverbal communication has been well established through several theories including Albert Mehrabian's 7-38-55 rule that proposes the respective importance of semantics, tonality and facial expressions in communication. Although several studies have examined how emotions are expressed and preceived in communication, there is limited research investigating the relationship between how emotions are expressed through semantics and facial expressions. Using a facial expression analysis software to deconstruct facial expressions into features and a K-Nearest-Neighbor (KNN) machine learning classifier, we explored if facial expressions can be clustered based on semantics. Our findings indicate that facial expressions can be clustered based on semantics and that there is an inherent congruence between facial expressions and semantics. These results are novel and significant in the context of nonverbal communication and are applicable to several areas of research including the vast field of emotion AI and machine emotional communication.
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