UT Southwestern Electronic Theses and Dissertations
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Browsing UT Southwestern Electronic Theses and Dissertations by Subject "Accidental Falls"
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Item Cognitive and Behavioral Predictors of Fall Risk in Parkinson Disease(2015-07-24) Denney, David Austin; Lacritz, Laura H.; Cullum, C. Munro; Hynan, Linda S.; Patel, Neepa; Ruchinskas, RobertFalls and their related injuries are a significant health issue for individuals with Parkinson disease (PD). Several factors have been identified that increase fall risk, including cognitive impairment, impulsiveness, and lower balance confidence, as well as PD-related characteristics. However, to date, no definitive predictor profile has been identified. As a result, there is a need to develop a comprehensive model incorporating elements from each of the areas known to have a relationship with fall behaviors in PD. Such information could result in improved identification and treatment of PD patients at higher risk of falls. This study used stepwise logistic regression analyses to identify predictors of retrospectively reported falls from four domains, which included separate cognitive, impulsiveness/impulsive-compulsive disorder (ICD) related behaviors, disease characteristics, and balance confidence models. Each stepwise logistic regression yielded significant results (p < .20), and all of the significant predictor variables were included in a fifth combined model. The combined stepwise logistic regression was significant for postural instability (odds ratio = 8.66), verbal learning (California Verbal Learning Test-2 Total Learning T Score [CVLT-II]) (odds ratio = 0.95), and self-reported behavioral impulsiveness (Barratt Impulsiveness Scale-11 [BIS-11]) (odds ratio = 1.10). Model comparisons using net reclassification improvement (NRI) and the Hanley and McNeil (1983) method were conducted to determine if the combined model was significantly better at predicting fall risk than the domain-specific models. The combined model had the highest rate of accurately predicting fall risk (83%); however, the combined model was not significantly better at predicting fall risk than the impulsiveness/ICD or balance confidence models. These results showed that postural instability was the best predictor of fall risk; however, incorporating cognitive and impulsiveness measures improved prediction of fall risk. In light of these findings, screening for impulsiveness and, when possible, verbal learning, could be incorporated into routine clinical PD evaluations for better identification of patients at higher risk of falls.Item Gamification of Exercise and Its Application for Fall Prevention Among Patients with Diabetes and Peripheral Neuropathy(2016-04-04) Martin, Elizabeth Monier; Nwariaku, Fiemu; Niwagaba, Lillian; Salazar, AdrianBACKGROUND: Individuals with diabetic peripheral neuropathy (DPN) often experience concomitant impaired proprioception and postural instability. Diminished peripheral sensory input, as found in DPN, has been associated with an increased risk of falling in elderly diabetics. Conventional balance training often consisting of Tai Chi, physiotherapy, and strength training has demonstrated an improvement in effective balance control for DPN patients, but these conditioning regimens do not provide visual feedback to help compensate for impaired proprioception. METHODS: In a randomized trial study, the efficacy of an innovative game-based balance and proprioception training program for patients with DPN was assessed through direct evaluation of changes in body sway before and after the exercise protocol using body worn sensor technology. Participants were randomized to either intervention or sham groupings. All participants' baseline gait and balance were assessed at the initial visit and again after four weeks. Twice weekly, the intervention group participated in a training regimen based on virtual simulation for a total of four weeks. Postural sway was assessed before and after each training session. The gaming exercise consisted of a series of ankle point-to-point reaching tasks as well as crossing a series of virtual obstacles of varying heights. During exercise training, the body-mounted sensors connected to the created program to produce real-time animation of lower extremity joint position for the participant to view on a computer monitor. RESULTS: Forty-one eligible subjects have been recruited to date; however, the results of 15 participants (Age: 56.3 ± 4.9, BMI: 30 ± 15 kg/m2) who completed the four-week exercise program have been reported. The preliminary results suggest that the active group reduced ankle sway by 76% (2.82 ± 2.8° to 0.66 ± 0.47°), hip sway by 81% (7.96 ± 9° to 1.48 ± 1.2°) and center of mass (COM) sway by 76% (0.69 ± 0.7° to 0.16 ± 0.11°) during eyes open balance assessment. Similar reductions during eyes closed assessments were observed with reductions of 50%, 24% and 45% for ankle, hip and COM sway, respectively. CONCLUSION: This research implemented a novel balance rehabilitation strategy for patients with diabetic peripheral neuropathy based on virtual reality technology that helps compensate for impaired joint proprioception. The method employed body sensors to generate an interactive user interface for real-time visual feedback based on ankle-joint motion, similar to a video game. The study provides evidence that visual illustration of extremity position in an interactive setting coupled with motor control tasks may be an effective rehabilitation method for postural instability in patients with diabetic peripheral neuropathy.