18,896 research outputs found

    A virtual reality game-like tool for assessing the risk of falling in the elderly

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    © 2019 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). In recent years, the use of interactive game technology has gained much interest in the research community as a means to measure indicators associated with the risk of falling in the elderly. Input devices used for gaming offer an inexpensive but yet reliable alternative to the costly apparatuses used in clinics and medical centers. In this paper, we explore the feasibility of using virtual reality technology as a tool to assess the risk of falling in the senior community in a more immersive, intuitive and descriptive manner. Our VR-based tool captures stepping performance parameters in order to fulfill the requirements of a well-established clinical test for fall risk assessment. The use of virtual reality allows for an immersive experience where elderly users can fully concentrate on the motor and cognitive functions being assessed rather than the technology being used

    Assessing the validity of in-game stepping performance data from a kinect-based fall prevention exergame

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    © 2018 IEEE. One of the main limitations of commercial games is the inability to determine improvements in the mental and physical health of the players. Although high game scores might provide an indication of higher cognitive and physical abilities, these are not sufficient to reliably determine the improvement in health outcomes. The work presented in this paper hence focuses on determining whether the collection of clinical measures during gameplay could potentially be used as a reliable indicator of improvement. For this study, the author uses the StepKinnection game for fall prevention, a Kinect-based game which builds on a hybrid version of the Choice Stepping Reaction Time (CSRT) task, a validated test that has been shown to prospectively predict older fallers. A group of 10 independent-living older adults was recruited and asked played with the game for a 12 weeks period of time. Assessments were conducted at baseline and every four weeks. Stepping performance data collected through gameplay was compared to the validated CSRT test. Statistical analysis proved that the stepping performance data collected by the game correlated and agreed with the validated measures of the CSRT test, suggesting that this could be used as a reliable indicator for health improvements

    The use of interactive game technology to improve the physical health of the elderly : a serious game approach to reduce the risk of falling in older people

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    University of Technology Sydney. Faculty of Engineering and Information Technology.The elderly population is growing dramatically both in Australia and globally. With age, the human body undergoes a series of changes that can lead to decline in mental and physical health. Decline in motor functions increases the risk of developing health problems such as postural instability, balance disorders or simply having a fall. Falling is the main cause of disability and fatality among the elderly. Statistics show that one in three older adults might experience a fall every year. This could be prevented with regular exercise. Exercises with a walking component have proven to reduce falls by 40%. However, compliance with physical activity is often poor due to the mode of delivery, which is often unattractive. One approach that might help alleviate this is the use of commercial video games to engage the elderly in physical exercise. However, this practice may have undesirable results as such games are not designed to provide therapeutic support for the elderly but instead to entertain a much younger audience. This thesis aims to solve the above problem through the use of interactive game technology by testing that optimal results for the health of the elderly come from the combination of three elements: • the integration of a formal method to assess progress towards and the achievement of the desired health outcomes, • inclusion of meaningful tasks aligned with the specific health objectives • an appropriate game design through the use of user-centred design methodologies. Firstly, literature in the area of video games with health purposes for the elderly is reviewed to develop a clear understanding of the health issues and the research opportunities in the area. Secondly, a series of game prototypes is built and tested to investigate whether off-the-shelf game technology can be used to reliably perform a clinical test for fall risk assessment. Then a game is developed that aims to reduce the risk of falling by training a set of specific cognitive and physical functions that have been shown to be associated with falling. This prototype, known as the StepKinnection game, integrates the concept of an appropriate game design for the elderly, inclusion of meaningful tasks and the collection of stepping performance data. Thirdly, a series of studies on independent-living people aged 65 years and over are conducted. These studies confirmed the ability to reliably perform a clinical test using off-the-shelf game technology, the acceptance and ease of use of the StepKinnection game, and the potential of StepKinnection to reduce the risk of falling in the elderly. Finally, an analytical framework is developed for designing interactive games with health purposes for the elderly. This framework aims to assist the development of games aligned to particular health outcomes. This framework emphasises the importance of aligning the game goals to the expected health outcomes as well as the continuous assessment of progress and effectiveness

    Structural generative descriptions for time series classification

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    In this paper, we formulate a novel time series representation framework that captures the inherent data dependency of time series and that can be easily incorporated into existing statistical classification algorithms. The impact of the proposed data representation stage in the solution to the generic underlying problem of time series classification is investigated. The proposed framework, which we call structural generative descriptions moves the structural time series representation to the probability domain, and hence is able to combine statistical and structural pattern recognition paradigms in a novel fashion. Two algorithm instantiations based on the proposed framework are developed. The algorithms are tested and compared using different publicly available real-world benchmark data. Results reported in this paper show the potential of the proposed representation framework, which in the experiments investigated, performs better or comparable to state-of-the-art time series description techniques

    Distributed Classification of Traffic Anomalies Using Microscopic Traffic Variables

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    Periodotopy in the gerbil inferior colliculus: local clustering rather than a gradient map

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    Periodicities in sound waveforms are widespread, and shape important perceptual attributes of sound including rhythm and pitch. Previous studies have indicated that, in the inferior colliculus (IC), a key processing stage in the auditory midbrain, neurons tuned to different periodicities might be arranged along a periodotopic axis which runs approximately orthogonal to the tonotopic axis. Here we map out the topography of frequency and periodicity tuning in the IC of gerbils in unprecedented detail, using pure tones and different periodic sounds, including click trains, sinusoidally amplitude modulated (SAM) noise and iterated rippled noise. We found that while the tonotopic map exhibited a clear and highly reproducible gradient across all animals, periodotopic maps varied greatly across different types of periodic sound and from animal to animal. Furthermore, periodotopic gradients typically explained only about 10% of the variance in modulation tuning between recording sites. However, there was a strong local clustering of periodicity tuning at a spatial scale of ca. 0.5 mm, which also differed from animal to animal

    An Overrepresentation of High Frequencies in the Mouse Inferior Colliculus Supports the Processing of Ultrasonic Vocalizations

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    Mice are of paramount importance in biomedical research and their vocalizations are a subject of interest for researchers across a wide range of health-related disciplines due to their increasingly important value as a phenotyping tool in models of neural, speech and language disorders. However, the mechanisms underlying the auditory processing of vocalizations in mice are not well understood. The mouse audiogram shows a peak in sensitivity at frequencies between 15-25 kHz, but weaker sensitivity for the higher ultrasonic frequencies at which they typically vocalize. To investigate the auditory processing of vocalizations in mice, we measured evoked potential, single-unit, and multi-unit responses to tones and vocalizations at three different stages along the auditory pathway: the auditory nerve and the cochlear nucleus in the periphery, and the inferior colliculus in the midbrain. Auditory brainstem response measurements suggested stronger responses in the midbrain relative to the periphery for frequencies higher than 32 kHz. This result was confirmed by single- and multi-unit recordings showing that high ultrasonic frequency tones and vocalizations elicited responses from only a small fraction of cells in the periphery, while a much larger fraction of cells responded in the inferior colliculus. These results suggest that the processing of communication calls in mice is supported by a specialization of the auditory system for high frequencies that emerges at central stations of the auditory pathway

    Assessing the kinect’s capabilities to perform a time-based clinical test for fall risk assessment in older people

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    © 2014 IFIP International Federation for Information Processing. The Choice Stepping Reaction Time (CSRT) task is time-based clinical test that has shown to reliably predict falls in older adults. Its current mode of delivery involves the use of a custom-made dance mat device. This mat is a measurement tool that can reliably obtain step data to discriminate between fallers and non-fallers. One of the pitfalls of this test is that the technology in use still imposes an obstacle on the degree of freedom to be able to perform adaptive exercises suitable for the elderly. In this paper, we describe a Kinect-based system that measures stepping performance through the use of a hybrid version of the CSRT task. This study focuses on assessing this system’s capabilities to reliably measure a time-based clinical test of fall risk. Results showed a favorable correspondence and agreement between the two systems, suggesting that this platform could be potentially useful in the clinical practice
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