Search Results (1 - 3 of 3 Results)

Sort By  
Sort Dir
 
Results per page  

Ma, TaoA Framework for Modeling and Capturing Social Interactions
PhD, University of Cincinnati, 2015, Engineering and Applied Science: Electrical Engineering
The understanding of human behaviors in the scope of computer vision is beneficial to many different areas. Although great achievement has been made, human behavior research investigations are still targeted on isolated, low-level, and individual activities without considering other important factors, such as human-human interactions, human-object interactions, social roles, and surrounding environments. Numerous publications focus on recognizing a small number of individual activities from body motion features with pattern recognition models, and are satisfied with small improvements of recognition rate. Furthermore, methods employed in these investigations are far from being suitable to be used in real cases considering the complexity of human society. In order to address the issue, more attention should be paid on cognition level rather than feature level. In fact, for a deeper understanding of social behavior, there is a need to study its semantic meanings against the social contexts, known as social interaction understanding. A framework for detecting social interaction needs to be established to initiate the study. In addition to individual body motions, more factors, including body motions, social roles, voice, related objects, environment, and other individuals' behaviors were added to the framework. To meet the needs, this dissertation study proposed a 4-layered hierarchical framework to mathematically model social interactions, and then explored several challenging applications based on the framework to demonstrate the great value of the study. There are no existing multimodality social interaction datasets available for this research. Thus, in Research Topic I, two typical scenes were created with a total of 24 takes (a take means a shot for a scene) as social interaction dataset. Topic II introduced a 4-layered hierarchical framework of social interactions, which contained 1) feature layer, 2) simple behavior layer, 3) behavior sequence layer, and 4) pairwise social interaction layer, from down to top. The top layer eventually generated two persons' joint behaviors in the form of descriptions with semantic meanings. To deal with the recognition within each layer, different statistical models were adopted. In Topic III, three applications based on the social interaction framework were presented, including social engagement, interesting moment, and visualization. The first application measured how strong the interaction was between an interaction pair. The second one detected unusual (interesting) individual behaviors and interactions. The third application aimed to better visually represent data so that users can get access to useful information quickly. All experiments in Research Topic II and III were based on the social interaction dataset created for the study. Performance of different layers was evaluated by comparing the experiment results with those of existing literature. The framework was demonstrated to be able to successfully capture and model certain social interactions, which can be applied to other situations. The pairwise social interaction layer generated joint behaviors with high accuracy because of the coupling nature of the model. Exploration on social engagement, interesting moments, and visualization shows great practical value of the current research may stimulate discussions and intrigue more research studies in the area.

Committee:

William Wee, Ph.D. (Committee Chair); Raj Bhatnagar, Ph.D. (Committee Member); Chia Han, Ph.D. (Committee Member); Anca Ralescu, Ph.D. (Committee Member); Xuefu Zhou, Ph.D. (Committee Member)

Subjects:

Computer Engineering

Keywords:

Human behavior understanding;Social interaction;Machine learning;Computer vision;Interesting moment;Social engagement

Roberts, Amy RestorickA LONGITUDINAL STUDY OF THE INFLUENCE OF SOCIAL ENGAGEMENT ON QUALITY OF LIFE AMONG OLDER ADULTS LIVING IN SENIOR HOUSING
Doctor of Philosophy, Case Western Reserve University, 2013, Social Welfare
This dissertation aims to examine the cross-sectional and longitudinal relationships between social engagement and quality of life among older adults living in the independent apartments of continuing care retirement communities (CCRC’s). Data were drawn from the Erickson Life Study (Resnick et al., 2001; 2005), a five year panel study of 300 older adults living in four CCRC’s. Quality of life is a multidimensional concept defined as older adults’ “perceptions of their positions in life in the context of the culture and value systems in which they live, and in relation to their goals, expectations, standards, and concerns” (Bonomi et al., 2000; WHOQoL Group, 1994). Components of social engagement included four types of giving and receiving social support and participation in formal social activities organized by the retirement community. A life course perspective guided the study which integrated a theory of psychosocial development (Erikson, 1950, 1982/1997), activity theory (Lemon, Bengston, & Peterson, 1972), social exchange theory (Dowd, 1975), and the proactivity model of successful aging (Kahana & Kahana, 1996, 2003; Kahana, Kelley-Moore, & Kahana, 2012). Findings from this dissertation research made several contributions to the literature. After living in senior housing for a year, receiving more informational and tangible support was associated with a poorer quality of life, yet participating in formal group activities was related to better quality of life. The longitudinal latent growth model uncovered individual differences in the initial status of quality of life, and showed that quality of life declined for the group over time. Factors that explained initial differences in quality of life included providing social support, gender, housing site, and quality of life before moving to the CCRC. One component of social engagement—participating in a greater number of formal social activities organized by the CCRC—slowed the rate of decline in quality of life over time. Findings suggest that active engagement in organized social and leisure activities can have a long-term beneficial effect for older adults by forestalling the decline of quality of life. Implications for gerontological social work practice and policy recommendations are discussed.

Committee:

Kathryn Betts Adams (Committee Chair); Kathleen J. Farkas (Committee Member); M. C. "Terry" Hokenstad (Committee Member); Jung-won Lim (Committee Member); Camille B. Warner (Committee Member)

Subjects:

Social Work

Keywords:

older adults; social engagement; quality of life; activity participation; continuing care retirement community

Weber, Ashley MOxytocin: Biomarker of Affiliation and Neurodevelopment in Premature Infants
Doctor of Philosophy, The Ohio State University, 2016, Nursing
Extremely premature infants, born at 28 weeks gestation or less, are at greatest risk for poor neurodevelopmental outcomes. While survival of these infants has improved in the past decade, neurodevelopmental outcomes have not. Because early life experiences affect brain structure and function, the quality of these experiences is one of the most important factors affecting optimal development. Reliable markers of neurobiological processes underlying development are necessary so that research can accurately monitor mediators of neurodevelopmental outcomes. Oxytocin (OT) has the potential to be a neurobiological marker of social processes that offer neuroprotection for the infant. OT acts as a buffer for the stress response system and provides protection to the brain during inflammation, ischemia, or injury. OT has been strongly linked to neurodevelopmental outcomes in animal models, particularly those outcomes related to social cognition and emotion regulation. No studies measuring OT have been conducted in premature infants, nor has the association of oxytocin levels and neurodevelopment for these infants been investigated. The purpose of this study is to 1) describe OT levels in plasma, urine, and saliva in premature infants through 34 weeks gestation and 2) determine if OT levels vary with maternal-infant interaction, neurobehavioral organization, and infant stress exposure. Thirty-seven premature infants, born gestational ages 25-28 6/7 weeks, were longitudinally followed until 36 weeks gestation. Plasma and urine samples were collected at 14 days of life, then weekly until 34 weeks. Data on infant and environmental variables were abstracted from the electronic medical record. Infant social engagement behaviors was measured by the Parent-Child Early Relational Assessment, during a videotaped feeding when the infant was at one-quarter full oral feeds. Infant stress exposure was measured weekly by the Neonatal Infant Stressor Scale. Neurobehavioral organization was measured by the NICU Network Neurobehavioral Scale at 36 weeks gestation. Plasma OT levels significantly decreased with age, at a rate of 15% per week. Urine OT levels did not significantly change with age. However, more research is needed before concluding that urine is not an acceptable noninvasive measurement in this population. Both plasma and urine exhibited wide variability across age, but values were significantly stable within infants. Plasma and urinary OT levels were not correlated, both within and between infants. Moreover, OT levels were not related to infant social engagement behaviors or infant neurobehavioral organization. We hypothesize that the stressful nature of the NICU environment may contribute to decreasing OT in premature infants. Future research must replicate these results, as well as determine how stress and the NICU environment impact OT levels in premature infants. We also hypothesize that before the emergence of coordinated movements and behaviors, premature infants primarily socially interact with their caregivers through their physiology. Future research should investigate associations among the physiologic coregulation of a dyad, coregulation of dyadic behaviors, and infant neurodevelopment. OT may serve as an important biomarker when investigating the window of development that encompasses the infant’s transition from the biologic to the social world.

Committee:

Deborah Steward (Advisor); Tondi Harrison (Committee Chair); Abigail Shoben (Committee Member)

Subjects:

Neurobiology; Nursing; Psychobiology

Keywords:

oxytocin; premature infant; prematurity; neurodevelopment; mother-child relations; social engagement; self-regulation; brain development; affiliation; maternal-infant interaction; bonding; attachment; infant; neonate; NICU; stress; allostatic load