413 resultados para Monitor (Ironclad)


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Aim This study evaluated the validity of the OMNI Walk/Run Rating of Perceived Exertion (OMNI-RPE) scores with heart rate and oxygen consumption (VO2) for children and adolescents with cerebral palsy (CP). Method Children and adolescents with CP, aged 6 to 18 years and Gross Motor Function Classification System (GMFCS) levels I to III completed a physical activity protocol with seven trials ranging in intensity from sedentary to moderate-to-vigorous. VO2 and heart rate were recorded during the physical activity trials using a portable indirect calorimeter and heart rate monitor. Participants reported OMNI-RPE scores for each trial. Concurrent validity was assessed by calculating the average within-subject correlation between OMNI-RPE ratings and the two physiological indices. Results For the correlational analyses, 48 participants (22 males, 26 females; age 12y 6mo, SD 3y 4mo) had valid bivariate data for VO2 and OMNI-RPE, while 40 participants (21 males, 19 females; age 12y 5mo, SD 2y 9mo) had valid bivariate data for heart rate and OMNI-RPE. VO2 (r=0.80; 95% CI 0.66–0.88) and heart rate (r=0.83; 95% CI 0.70–0.91) were moderately to highly correlated to OMNI-RPE scores. No difference was found for the correlation of physiological data and OMNI-RPE scores across the three GMFCS levels. The OMNI-RPE scores increased significantly in a dose-response manner (F6,258=116.1, p<0.001) as exercise intensity increased from sedentary to moderate-to-vigorous. Interpretation OMNI-RPE is a clinically feasible option to monitor exercise intensity in ambulatory children and adolescents with CP.

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- Objective This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). - Methods Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. - Results Chronic disease risks were high (e.g. 97% high waist circumference [≥94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1–4=8,743[SD 2,867] steps/day; weeks 17–20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1–4=38[IQR 21]%; weeks 17–20=58[IQR 18]%). - Conclusions Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. - Implications Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.

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The treatment of large segmental bone defects remains a significant clinical challenge. Due to limitations surrounding the use of bone grafts, tissue-engineered constructs for the repair of large bone defects could offer an alternative. Before translation of any newly developed tissue engineering (TE) approach to the clinic, efficacy of the treatment must be shown in a validated preclinical large animal model. Currently, biomechanical testing, histology, and microcomputed tomography are performed to assess the quality and quantity of the regenerated bone. However, in vivo monitoring of the progression of healing is seldom performed, which could reveal important information regarding time to restoration of mechanical function and acceleration of regeneration. Furthermore, since the mechanical environment is known to influence bone regeneration, and limb loading of the animals can poorly be controlled, characterizing activity and load history could provide the ability to explain variability in the acquired data sets and potentially outliers based on abnormal loading. Many approaches have been devised to monitor the progression of healing and characterize the mechanical environment in fracture healing studies. In this article, we review previous methods and share results of recent work of our group toward developing and implementing a comprehensive biomechanical monitoring system to study bone regeneration in preclinical TE studies.

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Environmental changes have put great pressure on biological systems leading to the rapid decline of biodiversity. To monitor this change and protect biodiversity, animal vocalizations have been widely explored by the aid of deploying acoustic sensors in the field. Consequently, large volumes of acoustic data are collected. However, traditional manual methods that require ecologists to physically visit sites to collect biodiversity data are both costly and time consuming. Therefore it is essential to develop new semi-automated and automated methods to identify species in automated audio recordings. In this study, a novel feature extraction method based on wavelet packet decomposition is proposed for frog call classification. After syllable segmentation, the advertisement call of each frog syllable is represented by a spectral peak track, from which track duration, dominant frequency and oscillation rate are calculated. Then, a k-means clustering algorithm is applied to the dominant frequency, and the centroids of clustering results are used to generate the frequency scale for wavelet packet decomposition (WPD). Next, a new feature set named adaptive frequency scaled wavelet packet decomposition sub-band cepstral coefficients is extracted by performing WPD on the windowed frog calls. Furthermore, the statistics of all feature vectors over each windowed signal are calculated for producing the final feature set. Finally, two well-known classifiers, a k-nearest neighbour classifier and a support vector machine classifier, are used for classification. In our experiments, we use two different datasets from Queensland, Australia (18 frog species from commercial recordings and field recordings of 8 frog species from James Cook University recordings). The weighted classification accuracy with our proposed method is 99.5% and 97.4% for 18 frog species and 8 frog species respectively, which outperforms all other comparable methods.

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Network data packet capture and replay capabilities are basic requirements for forensic analysis of faults and security-related anomalies, as well as for testing and development. Cyber-physical networks, in which data packets are used to monitor and control physical devices, must operate within strict timing constraints, in order to match the hardware devices' characteristics. Standard network monitoring tools are unsuitable for such systems because they cannot guarantee to capture all data packets, may introduce their own traffic into the network, and cannot reliably reproduce the original timing of data packets. Here we present a high-speed network forensics tool specifically designed for capturing and replaying data traffic in Supervisory Control and Data Acquisition systems. Unlike general-purpose "packet capture" tools it does not affect the observed network's data traffic and guarantees that the original packet ordering is preserved. Most importantly, it allows replay of network traffic precisely matching its original timing. The tool was implemented by developing novel user interface and back-end software for a special-purpose network interface card. Experimental results show a clear improvement in data capture and replay capabilities over standard network monitoring methods and general-purpose forensics solutions.

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OBJECTIVE To develop a short and easy to use questionnaire to measure use and usability of custom-made orthopaedic shoes, and to investigate its reproducibility. DESIGN Development of the questionnaire (Monitor Orthopaedic Shoes) was based on a literature search, expert interviews, 2 expert meetings, and exploration and testing of reproducibility. The questionnaire comprises 2 parts: a pre part, measuring expectations; and a post part, measuring experiences. Patients The pre part of the final version was completed twice by 37 first-time users before delivery of their orthopaedic shoes. The post part of the final version was completed twice by 39 first-time users who had worn their orthopaedic shoes for 2–4 months. RESULTS High reproducibility scores (Cohen’s kappa > 0.60 or intra class correlation > 0.70) were found in all but one question of both parts of the final version of the Monitor Orthopaedic Shoes questionnaire. The smallest real difference on a visual analogue scale (100 mm) ranged from 21 to 50 mm. It took patients approximately 15 minutes to complete one part. CONCLUSION Monitor Orthopaedic Shoes is a practical and reproducible questionnaire that can measure relevant aspects of use and usability of orthopaedic shoes from a patient’s perspective.

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Recommendations - 1 To identify a person with diabetes at risk for foot ulceration, examine the feet annually to seek evidence for signs or symptoms of peripheral neuropathy and peripheral artery disease. (GRADE strength of recommendation: strong; Quality of evidence: low) - 2 In a person with diabetes who has peripheral neuropathy, screen for a history of foot ulceration or lower-extremity amputation, peripheral artery disease, foot deformity, pre-ulcerative signs on the foot, poor foot hygiene and ill-fitting or inadequate footwear. (Strong; Low) - 3 Treat any pre-ulcerative sign on the foot of a patient with diabetes. This includes removing callus, protecting blisters and draining when necessary, treating ingrown or thickened toe nails, treating haemorrhage when necessary and prescribing antifungal treatment for fungal infections. (Strong; Low) - 4 To protect their feet, instruct an at-risk patient with diabetes not to walk barefoot, in socks only, or in thin-soled standard slippers, whether at home or when outside. (Strong; Low) - 5 Instruct an at-risk patient with diabetes to daily inspect their feet and the inside of their shoes, daily wash their feet (with careful drying particularly between the toes), avoid using chemical agents or plasters to remove callus or corns, use emollients to lubricate dry skin and cut toe nails straight across. (Weak; Low) - 6 Instruct an at-risk patient with diabetes to wear properly fitting footwear to prevent a first foot ulcer, either plantar or non-plantar, or a recurrent non-plantar foot ulcer. When a foot deformity or a pre-ulcerative sign is present, consider prescribing therapeutic shoes, custom-made insoles or toe orthosis. (Strong; Low) - 7 To prevent a recurrent plantar foot ulcer in an at-risk patient with diabetes, prescribe therapeutic footwear that has a demonstrated plantar pressure-relieving effect during walking (i.e. 30% relief compared with plantar pressure in standard of care therapeutic footwear) and encourage the patient to wear this footwear. (Strong; Moderate) - 8 To prevent a first foot ulcer in an at-risk patient with diabetes, provide education aimed at improving foot care knowledge and behaviour, as well as encouraging the patient to adhere to this foot care advice. (Weak; Low) - 9 To prevent a recurrent foot ulcer in an at-risk patient with diabetes, provide integrated foot care, which includes professional foot treatment, adequate footwear and education. This should be repeated or re-evaluated once every 1 to 3 months as necessary. (Strong; Low) - 10 Instruct a high-risk patient with diabetes to monitor foot skin temperature at home to prevent a first or recurrent plantar foot ulcer. This aims at identifying the early signs of inflammation, followed by action taken by the patient and care provider to resolve the cause of inflammation. (Weak; Moderate) - 11 Consider digital flexor tenotomy to prevent a toe ulcer when conservative treatment fails in a high-risk patient with diabetes, hammertoes and either a pre-ulcerative sign or an ulcer on the distal toe. (Weak; Low) - 12 Consider Achilles tendon lengthening, joint arthroplasty, single or pan metatarsal head resection, or osteotomy to prevent a recurrent foot ulcer when conservative treatment fails in a high-risk patient with diabetes and a plantar forefoot ulcer. (Weak; Low) - 13 Do not use a nerve decompression procedure in an effort to prevent a foot ulcer in an at-risk patient with diabetes, in preference to accepted standards of good quality care. (Weak; Low)

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Unhealthy diets contribute at least 14% to Australia's disease burden and are driven by ‘obesogenic’ food environments. Compliance with dietary recommendations is particularly poor amongst disadvantaged populations including low socioeconomic groups, those living in rural/remote areas and Aboriginal and Torres Strait Islanders. The perception that healthy foods are expensive is a key barrier to healthy choices and a major determinant of diet-related health inequities. Available state/regional/local data (limited and non-comparable) suggests that, despite basic healthy foods not incurring GST, the cost of healthy food is higher and has increased more rapidly than unhealthy food over the last 15 years in Australia. However, there were no nationally standardised tools or protocols to benchmark, compare or monitor food prices and affordability in Australia. Globally, we are leading work to develop and test approaches to assess the price differential of healthy and less-healthy (current) diets under the food price module of the International Network for Food and Obesity/non-communicable diseases (NCDs) Research, Monitoring and Action Support (INFORMAS). This presentation describes contextualization of the INFORMAS approach to develop standardised Australian tools, survey protocols and data collection and analysis systems. The ‘healthy diet basket’ was based on the Australian Foundation Diet, 1 The ‘current diet basket’ and specific items included in each basket, were based on recent national dietary survey data.2 Data collection methods were piloted. The final tools and protocols were then applied to measure the price and affordability of healthy and less healthy (current) diets of different household groups in diverse communities across the nation. We have compared results for different geographical locations/population subgroups in Australia and assessed these against international INFORMAS benchmarks. The results inform the development of policy and practice, including those relevant to mooted changes to the GST base, to promote nutrition and healthy weight and prevent chronic disease in Australia.

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Honey bees are in decline, and the current method of keeping them can be disruptive to a colony. But new designs allow beekeepers to monitor a hive remotely, even sniff out disease and pests.

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Background Child maltreatment has severe short-and long-term consequences for children’s health, development, and wellbeing. Despite the provision of child protection education programs in many countries, few have been rigorously evaluated to determine their effectiveness. We describe the design of a multi-site gold standard evaluation of an Australian school-based child protection education program. The intervention has been developed by a not-for-profit agency and comprises 5 1-h sessions delivered to first grade students (aged 5–6 years) in their regular classrooms. It incorporates common attributes of effective programs identified in the literature, and aligns with the Australian education curriculum. Methods/Design A three-site cluster randomised controlled trial (RCT) of Learn to be safe with Emmy and friends™ will be conducted with children in approximately 72 first grade classrooms in 24 Queensland primary (elementary) schools from three state regions, over a period of 2 years. Entire schools will be randomised, using a computer generated list of random numbers, to intervention and wait-list control conditions, to prevent contamination effects across students and classes. Data will be collected at baseline (pre-assessment), immediately after the intervention (post-assessment), and at 6-, 12-, and 18-months (follow-up assessments). Outcome assessors will be blinded to group membership. Primary outcomes assessed are children’s knowledge of program concepts; intentions to use program knowledge, skills, and help-seeking strategies; actual use of program material in a simulated situation; and anxiety arising from program participation. Secondary outcomes include a parent discussion monitor, parent observations of their children’s use of program materials, satisfaction with the program, and parental stress. A process evaluation will be conducted concurrently to assess program performance. Discussion This RCT addresses shortcomings in previous studies and methodologically extends research in this area by randomising at school-level to prevent cross-learning between conditions; providing longer-term outcome assessment than any previous study; examining the degree to which parents/guardians discuss intervention content with children at home; assessing potential moderating/mediating effects of family and child demographic variables; testing an in-vivo measure to assess children’s ability to discriminate safe/unsafe situations and disclose to trusted adults; and testing enhancements to existing measures to establish greater internal consistency.

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With society now recognizing that senior schooling is about flexibility in credentialing rather than a one-size-fits-all academic education, it has become necessary to track students through numerous pathways. This case study describes how Nambour State High School put into place a senior schooling tracking program which brought about cultural change throughout the school. Using the Tracking and Academic Management Index as a cohort tracking tool, the school has been able to monitor its senior schooling academic and non-academic performance over the past four years. By focusing on the four measures which make up the Index, Nambour State High School was able to demonstrate improved outcomes for all students in their senior school cohort.

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This research investigates techniques to analyse long duration acoustic recordings to help ecologists monitor birdcall activities. It designs a generalized algorithm to identify a broad range of bird species. It allows ecologists to search for arbitrary birdcalls of interest, rather than restricting them to just a very limited number of species on which the recogniser is trained. The algorithm can help ecologists find sounds of interest more efficiently by filtering out large volumes of unwanted sounds and only focusing on birdcalls.

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ARTIST STATEMENT VIBRANTe 2.0 was inspired by a research project for Parkinson’s disease patients aimed at developing a wearable device to collect relevant data for patients and medical health professionals. Vibrante is a Spanish word that translates to vibrant; literally meaning shaking or vibrations. Vibrante also has a dual meaning including vibrancy, energy, activity, and liveliness. Parkinson’s can be a debilitating disease, but it does not mean the person has to lose energy, activeness or vibrancy. As technology moves from being worn to becoming implantable and completely hidden within the body, the very notion of its physicality becomes difficult to grasp. While the human body hides implantable technology, VIBRANTe 2.0 intentionally hides the human body by making it invisible to reveal the technology stitched within. Wires become veins, delivering lifeblood to the technology inside, allowing it to pulsate and exist, while motherboards become networked hubs by which information is transferred through and within the body, performing functions that mirror and often surpass human performance capabilities. Ultimately, VIBRANTe 2.0 seeks to prompt the viewer to reflect on the potential ramifications of the complete immersion of technology into the human body. CONTEXT Technology is increasingly penetrating all aspects of our environment, and the rapid uptake of devices that live near, on or in our bodies is facilitating radical new ways of working, relating and socialising. Such technology, with its capacity to generate previously unimaginable levels of data, offers the potential to provide life-augmenting levels of interactivity. However, the absorption of technology into the very fabric of clothes, accessories and even bodies begins to dilute boundaries between physical, technological and social spheres, generating genuine ethical and privacy concerns and potentially having implications for human evolution. Embedding technology into the fabric of our clothes, accessories, and even the body enable the acquisition of and the connection to vast amounts of data about people and environments in order to provide life-augmenting levels of interactivity. Wearable sensors for example, offer the potential for significant benefits in the future management of our wellbeing. Fitness trackers such as ‘Fitbit’ and ‘Garmen’ provide wearers with the ability to monitor their personal fitness indicators while other wearables provide healthcare professionals with information that improves diagnosis and observation of medical conditions. This exhibition aimed to illustrate this shifting landscape through a selection of experimental wearable and interactive works by local, national and international artists and designers. The exhibition will also provide a platform for broader debate around wearable technology, our mediated future-selves and human interactions in this future landscape. EXHIBITION As part of Artisan’s Wearnext exhibition, the work was on public display from 25 July to 7 November 2015 and received the following media coverage: [Please refer to Additional URLs]

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Technology is increasingly infiltrating all aspects of our lives and the rapid uptake of devices that live near, on or in our bodies are facilitating radical new ways of working, relating and socialising. This distribution of technology into the very fabric of our everyday life creates new possibilities, but also raises questions regarding our future relationship with data and the quantified self. By embedding technology into the fabric of our clothes and accessories, it becomes ‘wearable’. Such ‘wearables’ enable the acquisition of and the connection to vast amounts of data about people and environments in order to provide life-augmenting levels of interactivity. Wearable sensors for example, offer the potential for significant benefits in the future management of our wellbeing. Fitness trackers such as ‘Fitbit’ and ‘Garmen’ provide wearers with the ability to monitor their personal fitness indicators while other wearables provide healthcare professionals with information that improves diagnosis. While the rapid uptake of wearables may offer unique and innovative opportunities, there are also concerns surrounding the high levels of data sharing that come as a consequence of these technologies. As more ‘smart’ devices connect to the Internet, and as technology becomes increasingly available (e.g. via Wi-Fi, Bluetooth), more products, artefacts and things are becoming interconnected. This digital connection of devices is called The ‘Internet of Things’ (IoT). IoT is spreading rapidly, with many traditionally non-online devices becoming increasingly connected; products such as mobile phones, fridges, pedometers, coffee machines, video cameras, cars and clothing. The IoT is growing at a rapid rate with estimates indicating that by 2020 there will be over 25 billion connected things globally. As the number of devices connected to the Internet increases, so too does the amount of data collected and type of information that is stored and potentially shared. The ability to collect massive amounts of data - known as ‘big data’ - can be used to better understand and predict behaviours across all areas of research from societal and economic to environmental and biological. With this kind of information at our disposal, we have a more powerful lens with which to perceive the world, and the resulting insights can be used to design more appropriate products, services and systems. It can however, also be used as a method of surveillance, suppression and coercion by governments or large organisations. This is becoming particularly apparent in advertising that targets audiences based on the individual preferences revealed by the data collected from social media and online devices such as GPS systems or pedometers. This type of technology also provides fertile ground for public debates around future fashion, identity and broader social issues such as culture, politics and the environment. The potential implications of these type of technological interactions via wearables, through and with the IoT, have never been more real or more accessible. But, as highlighted, this interconnectedness also brings with it complex technical, ethical and moral challenges. Data security and the protection of privacy and personal information will become ever more present in current and future ethical and moral debates of the 21st century. This type of technology is also a stepping-stone to a future that includes implantable technology, biotechnologies, interspecies communication and augmented humans (cyborgs). Technologies that live symbiotically and perpetually in our bodies, the built environment and the natural environment are no longer the stuff of science fiction; it is in fact a reality. So, where next?... The works exhibited in Wear Next_ provide a snapshot into the broad spectrum of wearables in design and in development internationally. This exhibition has been curated to serve as a platform for enhanced broader debate around future technology, our mediated future-selves and the evolution of human interactions. As you explore the exhibition, may we ask that you pause and think to yourself, what might we... Wear Next_? WEARNEXT ONLINE LISTINGS AND MEDIA COVERAGE: http://indulgemagazine.net/wear-next/ http://www.weekendnotes.com/wear-next-exhibition-gallery-artisan/ http://concreteplayground.com/brisbane/event/wear-next_/ http://www.nationalcraftinitiative.com.au/news_and_events/event/48/wear-next http://bneart.com/whats-on/wear-next_/ http://creativelysould.tumblr.com/post/124899079611/creative-weekend-art-edition http://www.abc.net.au/radionational/programs/breakfast/smartly-dressed-the-future-of-wearable-technology/6744374 http://couriermail.newspaperdirect.com/epaper/viewer.aspx RADIO COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 TELEVISION COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 https://au.news.yahoo.com/video/watch/29439742/how-you-could-soon-be-wearing-smart-clothes/#page1

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Aim To describe glycaemia in both breastfeeding women and artificially feeding women with Type 1 diabetes, and the changes in glycaemia induced by suckling. Methods A blinded continuous glucose monitor was applied for up to 6 days in eight breastfeeding and eight artificially feeding women with Type 1 diabetes 2–4 months postpartum. Women recorded glucose levels, insulin dosages, oral intake and breastfeeding episodes. A standardized breakfast was consumed on 2 days. A third group (clinic controls) were identified from a historical database. Results Carbohydrate intake tended to be higher in breastfeeding than artificially feeding women (P = 0.09) despite similar insulin requirements. Compared with breastfeeding women, the high blood glucose index and standard deviation of glucose were higher in artificially feeding women (P = 0.02 and 0.06, respectively) and in the clinical control group (P = 0.02 and 0.05, respectively). The low blood glucose index and hypoglycaemia were similar. After suckling, the low blood glucose index increased compared with before (P < 0.01) and during (P < 0.01) suckling. Hypoglycaemia (blood glucose < 4.0 mmol/l) occurred within 3 h of suckling in 14% of suckling episodes, and was associated with time from last oral intake (P = 0.04) and last rapid-acting insulin (P = 0.03). After a standardized breakfast, the area under the glucose curve was positive. In breastfeeding women the area under the glucose curve was positive if suckling was avoided for 1 h after eating and negative if suckling occurred within 30 min of eating. Conclusions Breastfeeding women with Type 1 diabetes had similar hypoglycaemia but lower glucose variability than artificially feeding women. Suckling reduced maternal glucose levels but did not cause hypoglycaemia in most episodes.