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Comparative optimism about falling amongst community-dwelling older South Australians: a mixed methods approach.Dollard, Joanne January 2009 (has links)
People aged ≥65 years (older people) have a higher chance of falling than other age groups. However, based on qualitative research, older people do not believe that falls prevention information and strategies have personal relevance. This suggests that older people believe that falls are more likely to happen to other older people than themselves, that is, they might be comparatively optimistic about their chance of falling. It is important to understand comparative optimism about falling as it is a consistent reason given by older people for not participating in falls prevention activity. This thesis used a mixed methods design with a sequential strategy to investigate community-dwelling older people's comparative optimism about falling. Three studies were undertaken, using semi-structured interviews, cognitive interviews and telephone interviews to collect data. The semi-structured interview study, guided by the tenets of grounded theory, aimed to develop an explanation of why older people might be comparatively optimistic. A sampling frame (age, sex and direct and indirect history of falling) was used to guide recruiting respondents. Older people (N = 9) were interviewed about their chance and other older people's chance of falling. Interviews were analysed using the constant comparison method. The cognitive interview study investigated potential problems in survey items in order to refine them for the telephone interview study. Items were developed to measure older people's comparative optimism about falling. Older people (N = 13) were cognitively interviewed, and interviews were content analysed. The telephone interview study aimed to determine whether older people were comparatively optimistic about falling, and whether the direct and indirect experience of falling was associated with comparative optimism. A random sample of older people (N = 389) living in South Australia were telephone interviewed (response rate = 75%). The semi-structured interview study identified that it was a 'threat to identity' for respondents to say they had a chance of falling because of intrinsic risk factors. Respondents used strategies to maintain or protect their identity when discussing their chance of falling in the future or their reasons for falling in the past. In the cognitive interview study, respondents reported difficulty in rating their chance of falling, as they believed falls were unexpected and unpredictable. They reported difficulty in rating other people's chance of falling, as they believed they did not know other people their age, did not have enough information and/or did not know the answer. In the telephone interview study, most respondents believed they had the same chance (42%), or a lower chance (48%) of falling in the next 12 months, than other older people. Having fallen in the last 12 months was significantly associated with a lowered comparative optimism, but knowing other older people who had fallen was not associated with comparative optimism. This is the first quantitative study to report that the majority of a representative sample of community-dwelling older people were comparatively optimistic about their chance of falling. Self-presentation concerns about having a chance of falling support the core category to emerge from the semi-structured interview study. Messages such as 'you can reduce your risk of falls' may be ignored by older people. Alternative messages should promote identities that are relevant to older people, such as being independent, mobile and active, but these messages should be tested in further research. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1374964 / Thesis (Ph.D.) - University of Adelaide, School of Psychology and School of Population Health and Clinical Practice, 2009
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Comparative optimism about falling amongst community-dwelling older South Australians: a mixed methods approach.Dollard, Joanne January 2009 (has links)
People aged ≥65 years (older people) have a higher chance of falling than other age groups. However, based on qualitative research, older people do not believe that falls prevention information and strategies have personal relevance. This suggests that older people believe that falls are more likely to happen to other older people than themselves, that is, they might be comparatively optimistic about their chance of falling. It is important to understand comparative optimism about falling as it is a consistent reason given by older people for not participating in falls prevention activity. This thesis used a mixed methods design with a sequential strategy to investigate community-dwelling older people's comparative optimism about falling. Three studies were undertaken, using semi-structured interviews, cognitive interviews and telephone interviews to collect data. The semi-structured interview study, guided by the tenets of grounded theory, aimed to develop an explanation of why older people might be comparatively optimistic. A sampling frame (age, sex and direct and indirect history of falling) was used to guide recruiting respondents. Older people (N = 9) were interviewed about their chance and other older people's chance of falling. Interviews were analysed using the constant comparison method. The cognitive interview study investigated potential problems in survey items in order to refine them for the telephone interview study. Items were developed to measure older people's comparative optimism about falling. Older people (N = 13) were cognitively interviewed, and interviews were content analysed. The telephone interview study aimed to determine whether older people were comparatively optimistic about falling, and whether the direct and indirect experience of falling was associated with comparative optimism. A random sample of older people (N = 389) living in South Australia were telephone interviewed (response rate = 75%). The semi-structured interview study identified that it was a 'threat to identity' for respondents to say they had a chance of falling because of intrinsic risk factors. Respondents used strategies to maintain or protect their identity when discussing their chance of falling in the future or their reasons for falling in the past. In the cognitive interview study, respondents reported difficulty in rating their chance of falling, as they believed falls were unexpected and unpredictable. They reported difficulty in rating other people's chance of falling, as they believed they did not know other people their age, did not have enough information and/or did not know the answer. In the telephone interview study, most respondents believed they had the same chance (42%), or a lower chance (48%) of falling in the next 12 months, than other older people. Having fallen in the last 12 months was significantly associated with a lowered comparative optimism, but knowing other older people who had fallen was not associated with comparative optimism. This is the first quantitative study to report that the majority of a representative sample of community-dwelling older people were comparatively optimistic about their chance of falling. Self-presentation concerns about having a chance of falling support the core category to emerge from the semi-structured interview study. Messages such as 'you can reduce your risk of falls' may be ignored by older people. Alternative messages should promote identities that are relevant to older people, such as being independent, mobile and active, but these messages should be tested in further research. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1374964 / Thesis (Ph.D.) - University of Adelaide, School of Psychology and School of Population Health and Clinical Practice, 2009
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Balance Control and Stability during Gait - An Evaluation of Fall Risk among Elderly AdultsLugade, Vipul Anand, 1980- 09 1900 (has links)
xiii, 109 p. : ill. / Falls are a significant source of physical, social, and psychological suffering among elderly adults. Falls lead to morbidity and even mortality. Over one-third of adults over the age of 65 years will fall within a calendar year, with almost 10,000 deaths per year attributed to falls. The direct cost of falls exceeds $10 billion a year in the United States. Fall incidents have been linked to multiple risk factors, including cognitive function, muscle strength, and balance control. The ability to properly identify balance impairment is a tremendous challenge to the medical community, with accurate assessment of fall risk lacking. Therefore, the purpose of this study was to assess balance control during gait among young adults, elderly adults, and elderly fallers; determine which biomechanical measures can best identify fallers retrospectively; demonstrate longitudinal changes in elderly adults and prospectively assess fall risk; and provide a method for mapping clinical variables to sensitive balance control measures using artificial neural networks.
The interaction of the whole body center of mass (CoM) in relation to the base of support (BoS) assessed static and dynamic balance control throughout gait. Elderly fallers demonstrated reduced balance control ability, specifically a decreased time to contact with the boundary of the BoS, when compared to young adults at heel strike. This decreased time might predispose older adults to additional falls due to an inability to properly respond to perturbations or slips.
Inclusion of these balance control measures along with the Berg Balance Scale and spatiotemporal measures demonstrated sensitivity and specificity values of up to 90% when identifying 98 elderly fallers and non-fallers, respectively. Additionally, 27 older adults were followed longitudinally over a period of one year, with only the interaction of the CoM with the BoS demonstrating an ability to differentiate fallers and non-fallers prospectively.
As the collection and analysis of these biomechanics measures can be time consuming and expensive, an artificial neural network demonstrated that clinical measures can accurately predict balance control during ambulation. This model approached a solution quickly and provides a means for assessing longitudinal changes, intervention effects, and future fall risk.
This dissertation includes both previously published and unpublished co-authored material. / Committee in charge: Dr. Li-Shan Chou, Chair;
Dr. Andrew Karduna, Member;
Dr. Marjorie Woollacott, Member;
Dr. Ronald Stock, Member;
Dr. Arthur Farley, Outside Member
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A comparison of the levels of patient staffing ratios and staffing mix to the number of patient falls in an acute care settingPeters, Candice Marie 01 January 1997 (has links)
No description available.
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Integrated wireless sensor system for efficient pre-fall detectionTiwari, Nikhil 13 April 2015 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / The life expectancy of humans in today's era have increased to a very large extent due to the advancement of medical science and technology. The research in medical science has largely been focused towards developing methods and medicines to cure a patient after a diagnosis of an ailment. It is crucial to maintain the quality of life and health of the patient. It is of most importance to provide a healthy life to the elderly as this particular demographic is the most severely affected by health issues, which make them vulnerable to accidents, thus lowering their independence and quality of life. Due to the old age, most of the people become weak and inefficient in carrying their weight, this increases the probability of falling when moving around. This research of iterative nature focuses on developing a device which works as a preventive measure to reduce the damage due to a fall.
The research critically evaluates the best approach for the design of the Pre-Fall detection system. In this work, we develop two wearable Pre-Fall detection system with reduced hardware and practical design. One which provides the capability of logging the data on an SD card in CSV format so that the data can be analyzed, and second, capability to connect to the Internet through Wifi. In this work, data from multiple accelerometers attached at different locations of the body are analyzed in Matlab to find the optimum number of sensors and the best suitable position on the body that gives the optimum result.
In this work, a strict set of considerations are followed to develop a flexible, practical and robust prototype which can be augmented with different sensors without changing the fundamental design in order to further advance the research. The performance of the system to distinguish between fall and non-fall is improved by selecting and developing the most suitable way of calculating the body orientation. The different ways of calculating the orientation of the body are scrutinized and realized to compare the performance using the hardware. To reduce the number of false positives, the system considers the magnitude and the orientation to make a decision.
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Perceptions of residential grab bars among community dwelling seniorsThrall, Patti L. 04 June 2012 (has links)
Despite the perceived importance of grab bars to facilitate aging-in-place and healthy aging, many community-dwelling older adults do not have them installed. The aim of this study was to investigate predictors of grab bar installation among well-educated community dwelling seniors. Data was collected quantitatively through an electronic survey of Oregon residents 50 years of age and older. The research analysis was completed using logistic regression with SPSS and qualitative analysis for the open questions. / Graduation date: 2012
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Evaluating balance and strength of older women in exercise programsDinger, Melanie (Melanie Elizabeth) 15 February 2013 (has links)
Falls are a common problem among older adults, including those who are relatively healthy and living independently. Exercise has been recommended as an intervention to reduce falls by slowing and/or reversing age-related declines in balance, strength, and mobility. However, it remains unclear which types or combinations of programs are most effective. The objective of this study was to investigate whether exercise programs performed by healthy older adults were associated with superior balance, strength, and functional mobility measures that are pertinent to fall prevention.
This study compared three distinct groups: participants of a balance- and strength-focused training program (i.e., Better Bones and Balance®), participants engaged in a general walking program, and sedentary individuals. Balance was measured using the Sensory Organization Test composite score and sensory ratios. Isometric strength of the lateral hip stabilizers (i.e., abductors and adductors) was measured in terms of maximum voluntary contraction and rapid torque production. Rapid torque measures included contractile impulse and rate of torque development evaluated at 0-100 ms and 0-300 ms from contraction onset. Functional mobility was measured by the time to complete the Four Square Step Test.
Hip abduction contractile impulse (0-300 ms) was 1.905 Nm*s and 1.539 Nm*s higher for the Better Bones and Balance (BBB) group compared to the walking and sedentary groups, respectively. No differences were found among the groups for any of the hip adduction torque measures or Sensory Organization Test balance scores. The BBB group completed the Four Square Step Test faster than the walking and sedentary groups by 0.90 s and 1.06 s, respectively. In conclusion, participation in the balance- and strength-focused training program was associated with superior performance in some measures of strength and functional mobility that may be important for fall prevention. / Graduation date: 2013
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Vitamin D, neuromuscular control and falling episodes in Australian postmenopausal womenAustin, Nicole January 2009 (has links)
Falls in the older population have devastating consequences on the psychological and physiological health of the individual. Due to the complexity of interacting factors associated with ageing, pathology and falling episodes, determination of a primary cause or set of causes has been difficult to establish. Deficits in components of neuromuscular control have been widely studied with the coordinated interaction of sensory and motor system components being presented as a fundamental factor in the reduction of falling episodes. A causal relationship between deficits in vitamin D status and falling episodes has also been suggested. Furthermore, a relationship between poor vitamin D status, falling episodes and poor neuromuscular performance has been reported. The aims of the current study were designed to advance understanding in three aspects of the problem of falls prevention. Firstly an examination of the reliability of testing procedures commonly used in assessment of falls risk was undertaken. The Physiological Profile Assessment (PPA) testing procedure was selected as a commonly used tool and the reliability of its various components (sensory, motor and balance) was undertaken as an independent assessment of this approach to assessing falls propensity. Secondly, a case control study of fallers and non fallers was undertaken in which the neuromuscular tests evaluated in the reliability study were used to assess differences in neuromuscular control. The influence of vitamin D status on these measures was also considered. Thirdly, a 12-month randomised controlled trial of vitamin D/calcium supplementation or placebo/calcium was undertaken to identify the effect on falls outcome and individual measures of neuromuscular control.
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An integrated sensor system for early fall detectionBandi, Ajay Kumar 05 1900 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Physical activity monitoring using wearable sensors give valuable information about patient's neuro activities. Fall among ages of 60 and older in US is a leading cause for injury-related health issues and present serious concern in the public health care sector. If the emergency treatments are not on time, these injuries may result in disability, paralysis, or even death. In this work, we present an approach that early detect fall occurrences. Low power capacitive accelerometers incorporated with microcontroller processing units were utilized to early detect accurate information about fall events. Decision tree algorithms were implemented to set thresholds for data acquired from accelerometers. Data is then verified against their thresholds and the data acquisition decision unit makes the decision to save patients from fall occurrences. Daily activities are logged on an onboard memory chip with Bluetooth option to transfer the data wirelessly to mobile devices.
In this work, a system prototype based on neurosignal activities was built and tested against seven different daily human activities for the sake of differentiating between fall and non-fall detection. The developed system features low power, high speed, and high reliability. Eventually, this study will lead to wearable fall detection system that serves important need within the health care sector.
In this work Inter-Integrated Circuit (I2C) protocol is used to communicate between the accelerometers and the embedded control system. The data transfer from the Microcontroller unit to the mobile device or laptop is done using Bluetooth technology.
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Development and evaluation of an elderly fall detection system based on a wearable device located at wrist / Desenvolvimento e avaliação de um sistema de detecção de quedas de idosos baseado em um dispositivo vestível localizado no punhoQuadros, Thiago de 31 August 2017 (has links)
A queda de idosos é um problema de saúde mundial. Todos os anos, cerca de 30% dos idosos com 65 anos ou mais são vítimas de quedas. Além disso, as consequências de uma queda podem ser fisiológicas (e.g. fraturas ósseas, ferimentos musculares) e psicológicas, como a perda de autoconfiança, levando a novas quedas. Uma solução para este problema está relacionada com ações preventivas (e.g. adaptação de mobília) aliadas a sistemas de detecção de quedas, os quais podem notificar familiares e serviços médicos de urgência. Como o tempo de espera por socorro após uma queda está relacionado com a severidade das consequências dela, esses sistemas devem oferecer elevada acurácia e detecção em tempo real. Embora existam várias soluções para isso na literatura (a maioria relacionada com dispositivos vestíveis), poucas delas estão relacionadas a dispositivos de punho, principalmente por causa dos desafios existentes para essa configuração. Considerando o punho como um local mais confortável, discreto e aceitável para uso de um dispositivo (menos associado com o estigma do uso de uma solução médica), este trabalho propõe o desenvolvimento e avaliação de uma solução baseada nessa configuração. Para isso, diferentes sensores (acelerômetro, giroscópio e magnetômetro) foram combinados com diferentes algoritmos, baseados em métodos de limiar e aprendizado de máquina, visando definir os melhores sinais e abordagem para a detecção de quedas. Esses métodos consideraram informações de aceleração, velocidade, deslocamento e orientação espacial, permitindo o cálculo de componentes verticais do movimento. Para o treino e avaliação dos algoritmos, dois protocolos diferentes foram empregados: um primeiro envolvendo 2 voluntários (homens, 27 e 31 anos) simulando um total de 80 sinais de queda e 80 de não-queda, e um segundo envolvendo 22 voluntários (14/8 homens/mulheres, idade média: 25,2 ± 4,7) simulando um total de 396 sinais de queda e 396 de não-queda. Uma análise exaustiva de diferentes sinais e parâmetros de configuração foi executada para cada método. O melhor algoritmo baseado em limiar considerou sinais de aceleração vertical e velocidade total, alcançando 95,8% de sensibilidade e 86,5% de especificidade. Por outro lado, o melhor algoritmo de aprendizagem de máquina foi o baseado no método K-Nearest Neighbors, considerando informações de aceleração, velocidade e deslocamento verticais combinadas com os ângulos de orientação espacial: 100% de sensibilidade e 97,9% de especificidade. Os resultados obtidos permitem enfatizar a relevância de algoritmos de aprendizagem de máquina para sistemas de detecção de queda vestíveis localizados no punho quando comparados a algoritmos baseados em limiar. Esta conclusão oferece grande contribuição para a pesquisa de detectores de quedas similares, sugerindo a melhor abordagem para novos desenvolvimentos. / Falls in the elderly age are a world health problem. Every year, about 30% of people aged 65 or older become victims of fall events. The consequences of a fall may be physiological (e.g. bone fractures, muscular injuries) and psychological, including the loss of self-confidence by fear of falling, which leads to new falls. A solution to this problem is related to preventive actions (e.g. adapting furniture) allied to fall detection systems, which can alert family members and emergency medical services. Since the response time for help is related to the fall's consequences and severity, such systems must offer high accuracy and real-time fall detection. Although there are many fall detection solutions in literature (most part of them related to wearable devices), few of them are related to wrist-worn devices, mainly because of the existing challenges for this configuration. Considering the wrist as a comfortable, discrete and acceptable place for an elderly wearable device (less associated to the stigma of using a medical device), this work proposes the development and evaluation of a fall detection solution based on this configuration. For this, different sensors (accelerometer, gyroscope and magnetometer) were combined to different algorithms, based on threshold and machine learning methods, in order to define the best signals and approach for an elderly fall detection. These methods considered acceleration, velocity and displacement information, relating them with wrist spatial orientation, allowing the calculation of the vertical components of each movement. For the algorithms' training and evaluation, two different protocols were employed: one involving 2 volunteers (both males, ages of 27 and 31) performing a total of 80 fall and 80 non-fall events simulation, and the other involving 22 volunteers (14/8 males/females, ages mean: 25.2 ± 4.7) performing a total of 396 fall and 396 non-fall events simulation. An exhaustive evaluation of different signals and configuration parameters was performed for each method. The best threshold-based algorithm employed the vertical acceleration and total velocity signals, achieving 95.8% and 86.5% of sensitivity and specificity, respectively. On the other hand, the best machine learning algorithm was based on the K-Nearest Neighbors method employing the vertical acceleration, velocity and displacement information combined with spatial orientation angles: 100% of sensitivity and 97.9% of specificity. The obtained results allow to emphasize the relevance of machine learning algorithms for wrist-worn fall detection systems instead of traditional threshold-based algorithms. These results offer great contributions for the research of similar wearable fall detectors, suggesting the best approach for new developments.
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