13 research outputs found

    Postural motor learning and the effects of age on practice-related improvements in compensatory posture control

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    The purpose of this thesis was to examine the capacity for acquisition and retention of practice-related improvements in compensatory posture control and the nature of postural motor learning among healthy young and older adults repeatedly exposed to continuous surface motion via a translating platform. Although much research has been conducted to examine the strategies adopted by the central nervous system to control posture in response to external perturbations, the learning capabilities of this system have remained relatively unexplored. Many of the studies that have explored practice-related changes in balance performance have focused on short-term adaptations to highly predictable stimuli. Borrowing from implicit sequence learning paradigms, we developed two experimental protocols to examine postural motor learning for a compensatory balance task in an environment with limited predictability. Applying key principles of motor learning to our experimental design including retention intervals and a transfer task enabled us to draw conclusions about the permanency and specificity of the observed changes. Our investigations revealed practice-related changes in the motor organization of posture control. In young adults, a shift in the complexity of the control strategy occurred which lead to improvements in spatial and temporal control of the COM. In contrast, a majority of older adults persisted with a simplified control strategy which restricted improvements in COM control. Importantly, despite control strategy differences, the two groups showed comparable rates of improvement in almost all outcome measures including measures of trunk stability and temporal COM control. Longer-term retention of behavioural changes provided evidence for learning in young adults. Similar maintenance of improvements was observed for some outcome measures in older adults. Where significant losses in performance occurred in this group, retention was evident in the rapid reacquisition of performance to the level of proficiency achieved in original practice. Based on these results, we concluded that age affected the adapted control strategy but not the capacity for postural motor learning. Further, regardless of age or protocol, the pattern of postural perturbations did not influence acquisition of a strategy of stability and thus, we concluded that postural motor learning under the current conditions was non-specific, that is, it did not involve sequence-specific learning. These results provide important insight into the generalized nature of compensatory postural motor learning and subsequently, into the potential for positive transfer of balance skill to other balance tasks

    The OCareCloudS project: toward organizing care through trusted cloud services

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    The increasing elderly population and the shift from acute to chronic illness makes it difficult to care for people in hospitals and rest homes. Moreover, elderly people, if given a choice, want to stay at home as long as possible. In this article, the methodologies to develop a cloud-based semantic system, offering valuable information and knowledge-based services, are presented. The information and services are related to the different personal living hemispheres of the patient, namely the daily care-related needs, the social needs and the daily life assistance. Ontologies are used to facilitate the integration, analysis, aggregation and efficient use of all the available data in the cloud. By using an interdisciplinary research approach, where user researchers, (ontology) engineers, researchers and domain stakeholders are at the forefront, a platform can be developed of great added value for the patients that want to grow old in their own home and for their caregivers

    NiMBaLWear analytics pipeline for wearable sensors: a modular, open-source platform for evaluating multiple domains of health and behaviour

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    Abstract Background Recent technological advances have led to a surge in the use of wearable devices for personal health and fitness monitoring; however, clinical uptake of wearable devices for remote or ‘free-living’ measurement of daily health-related behavior has lagged. To advance the field, there is need for valid and reliable outcomes across multiple health domains specific to the cohorts or patients of interest and centralized tools to build capacity for use of these data. The NiMBaLWear pipeline provides a flexible and integrated approach to wearables analytics applied to raw sensor data that considers multiple, inter-related physiological and behavioral signals to provide a holistic view of health status. Results & discussion NiMBaLWear is a modular, open-source, wearable sensor analytic pipeline that quantifies physical activity, mobility, and sleep from raw single- or multi-sensor free-living data collected over multiple days. Data captured from any device, in different possible formats, are standardized prior to processing. Data preparation includes accelerometer autocalibration, cross-device synchronization, and non-wear detection. Validated, domain-specific algorithms detect events, generate outcome measures, and output standardized tabular data and user-friendly summary collection reports. NiMBaLWear was developed in Python using an iterative and incremental software development process, which included a combination of semi-automated inspection and expert review of data collected from 286 participants across two remote-measurement studies. A comparative analysis revealed a paucity of open-source packages capable of deriving and sharing health-related behavioral outcomes across multiple domains from multi-sensor wearables data. Forthcoming improvements to the pipeline will leverage sensor fusion techniques to add new, and refine existing, domain- and disease-specific analytics, and optimize pipeline accessibility and reporting. Conclusion The NiMBaLWear pipeline transforms raw multi-sensor wearables data into accurate and relevant outcomes across multiple health domains to objectively characterize and measure an individual’s daily health-related behavior. NiMBaLWear’s focus on high-quality, clinically relevant outcomes, as well as end-user optimization, provides a foundation for innovation to improve the utility of wearables for clinical care and self-management of health

    The OCareCloudS project: toward organizing care through trusted cloud services

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    The increasing elderly population and the shift from acute to chronic illness makes it difficult to care for people in hospitals and rest homes. Moreover, elderly people, if given a choice, want to stay at home as long as possible. In this article, the methodologies to develop a cloud-based semantic system, offering valuable information and knowledge-based services, are presented. The information and services are related to the different personal living hemispheres of the patient, namely the daily care-related needs, the social needs and the daily life assistance. Ontologies are used to facilitate the integration, analysis, aggregation and efficient use of all the available data in the cloud. By using an interdisciplinary research approach, where user researchers, (ontology) engineers, researchers and domain stakeholders are at the forefront, a platform can be developed of great added value for the patients that want to grow old in their own home and for their caregivers.peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=imif20status: publishe

    The SuperAging Research Initiative: A multisite consortium focused on identifying factors promoting extraordinary cognitive aging

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    BackgroundThe designation of SuperAger is reserved for individuals age 80+ who have episodic memory capacity that would be considered at least average for those 2-3 decades younger. The presence of such outliers raises questions of fundamental importance to the neurobiology of brain aging. Have these superior memory performers resisted age-related changes, or have they simply started from a much higher baseline? Do they have identifiable peculiarities of genetic background? Is there something special about their brain structure or perhaps their resistance to age-related processes such as neurofibrillary degeneration and amyloid deposition? These are the questions that were initially addressed by the Northwestern SuperAging Project, which identified unique results encompassing cognitive, psychosocial, molecular, and neuropathologic markers that characterize SuperAgers. Obstacles to further progress have been the relative rarity of this phenotype and, consequently, the barriers to racial diversity in the cohort.MethodsTo address these challenges, we established the SuperAging Research Initiative, a multicenter study focused on increased minority representation, to identify behavioral, health, biologic, genetic, environmental, socioeconomic, psychosocial, neuroanatomic, and neuropathologic factors associated with SuperAging.ResultsHere we provide the organizational structure and progress to date of the SuperAging Research Initiative, which includes three Cores (Administrative/Biostatistics, Clinical/Imaging, and Biospecimen/Neuropathology) and two Research Projects. Enrollment (n = 500) is planned across four US Sites located in Illinois, Wisconsin, Michigan, and Georgia, and a Canadian Site in Southwest Ontario, with a focus on enrollment of Black SuperAgers and Cognitively Average Elderly Controls with similar demographics. Project 1 uses state-of-the-art wearable technology to obtain quantitative everyday measurements of life sleep, physical activity, autonomic responsivity, and social engagement to determine whether SuperAgers have relatively preserved physiologic and behavioral ‘complexity’ compared to Controls. Project 2 focuses on transcriptomic, genetic, and protein profiling to examine central and peripheral immune and inflammatory system parameters of SuperAgers.ConclusionsBy identifying factors contributing to superior memory performance in old age, outcomes may help isolate modifiable factors that promote healthspan and perhaps also prevent age-related brain diseases such as Alzheimer’s disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/175507/1/alz066407.pd
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