How to build better fall detection technology : a search for characteristics unique to falls and methods to robustly evaluate performance

Falls can have severe consequences for older adults, such as bone fractures and long periods unable to get up from the ground, known as a long-lie. The capability to automatically detect falls would reduce long-lies through ensuring prompt arrival of assistance and would be valuable in fall risk assessment and fall prevention research. This research aimed to identify why existing wearable fall detection technology has not achieved acceptable performance and where further development should focus. There have been a plethora of attempts at fall detection; real-world testing is in an embryonic stage, nevertheless, it is clear performance has been poor. The focus has been on the testing of complete system performance, most commonly with acted falls, and it has been unclear how to improve performance. A new framework for the development of fall detection is proposed which promotes targeted investigation of how real-world performance can be improved. An improved method to quantify real-world performance is also proposed based on a systematic review of previous approaches. To prepare for the analysis of a real-world dataset, a pilot study was conducted which focused on the development and testing of posture classification algorithms. One of the world's largest datasets of real-world falls and activities of daily living was collected over 2 years in collaboration with 17 care homes across Scotland and the north of England. Twenty fall signals were extracted from 1,919 days of thigh-worn accelerometer recordings collected with 42 participants. Analysis of the data focused on falls from an upright to a sedentary (sitting or lying) posture, 16 falls met this criterion and were included in the analysis. To allow the data to be thoroughly checked for quality, the dataset was reduced to 104 days, from which 4,293 upright to sedentary transitions were extracted (including the 16 falls). This study was the first to: discern that falls may be too diverse to classify as a single group and focus on a subtype of fall, use posture transitions to select events for analysis, assess the importance of peak jerk and vertical velocity for fall detection, and investigate the occurrence of multiple impacts during falls. The results demonstrated that the core features used previously do not yield sufficient separation of the falls to allow detection without high rates of false positives. For the first time, it was shown that (1) a rapid increase in deceleration may be more indicative of a fall than the peak deceleration, and (2) multiple impacts occur frequently in falls but not other movements

Methods for the real-world evaluation of fall detection technology : a scoping review

Falls in older adults present a major growing healthcare challenge and reliable detection of falls is crucial to minimise their consequences. The majority of development and testing has used laboratory simulations. As simulations do not cover the wide range of real-world scenarios performance is poor when retested using real-world data. There has been a move from the use of simulated falls towards the use of real-world data. This review aims to assess the current methods for real-world evaluation of fall detection systems, identify their limitations and propose improved robust methods of evaluation. Twenty-three articles met the inclusion criteria and were assessed with regard to the composition of the datasets, data processing methods and the measures of performance. Real-world tests of fall detection technology are inherently challenging and it is clear the field is in it’s infancy. Most studies used small datasets and studies differed on how to quantify the ability to avoid false alarms and how to identify non-falls, a concept which is virtually impossible to define and standardise. To increase robustness and make results comparable, larger standardised datasets are needed containing data from a range of participant groups. Measures which depend on the definition and identification of non-falls should be avoided. Sensitivity, precision and F-measure emerged as the most suitable robust measures for evaluating the real-world performance of fall detection systems

Biodiversity of Mineral Nutrient and Trace Element Accumulation in Arabidopsis thaliana

In order to grow on soils that vary widely in chemical composition, plants have evolved mechanisms for regulating the elemental composition of their tissues to balance the mineral nutrient and trace element bioavailability in the soil with the requirements of the plant for growth and development. The biodiversity that exists within a species can be utilized to investigate how regulatory mechanisms of individual elements interact and to identify genes important for these processes. We analyzed the elemental composition (ionome) of a set of 96 wild accessions of the genetic model plant Arabidopsis thaliana grown in hydroponic culture and soil using inductively coupled plasma mass spectrometry (ICP-MS). The concentrations of 17–19 elements were analyzed in roots and leaves from plants grown hydroponically, and leaves and seeds from plants grown in artificial soil. Significant genetic effects were detected for almost every element analyzed. We observed very few correlations between the elemental composition of the leaves and either the roots or seeds. There were many pairs of elements that were significantly correlated with each other within a tissue, but almost none of these pairs were consistently correlated across tissues and growth conditions, a phenomenon observed in several previous studies. These results suggest that the ionome of a plant tissue is variable, yet tightly controlled by genes and gene×environment interactions. The dataset provides a valuable resource for mapping studies to identify genes regulating elemental accumulation. All of the ionomic data is available at www.ionomicshub.org

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Root Suberin Forms an Extracellular Barrier That Affects Water Relations and Mineral Nutrition in Arabidopsis

Though central to our understanding of how roots perform their vital function of scavenging water and solutes from the soil, no direct genetic evidence currently exists to support the foundational model that suberin acts to form a chemical barrier limiting the extracellular, or apoplastic, transport of water and solutes in plant roots. Using the newly characterized enhanced suberin1 (esb1) mutant, we established a connection in Arabidopsis thaliana between suberin in the root and both water movement through the plant and solute accumulation in the shoot. Esb1 mutants, characterized by increased root suberin, were found to have reduced day time transpiration rates and increased water-use efficiency during their vegetative growth period. Furthermore, these changes in suberin and water transport were associated with decreases in the accumulation of Ca, Mn, and Zn and increases in the accumulation of Na, S, K, As, Se, and Mo in the shoot. Here, we present direct genetic evidence establishing that suberin in the roots plays a critical role in controlling both water and mineral ion uptake and transport to the leaves. The changes observed in the elemental accumulation in leaves are also interpreted as evidence that a significant component of the radial root transport of Ca, Mn, and Zn occurs in the apoplast

How to use the world's scarce selenium resources efficiently to increase the selenium concentration in food

The world's rare selenium resources need to be managed carefully. Selenium is extracted as a by-product of copper mining and there are no deposits that can be mined for selenium alone. Selenium has unique properties as a semi-conductor, making it of special value to industry, but it is also an essential nutrient for humans and animals and may promote plant growth and quality. Selenium deficiency is regarded as a major health problem for 0.5 to 1 billion people worldwide, while an even larger number may consume less selenium than required for optimal protection against cancer, cardiovascular diseases and severe infectious diseases including HIV disease. Efficient recycling of selenium is difficult. Selenium is added in some commercial fertilizers, but only a small proportion is taken up by plants and much of the remainder is lost for future utilization. Large biofortification programmes with selenium added to commercial fertilizers may therefore be a fortification method that is too wasteful to be applied to large areas of our planet. Direct addition of selenium compounds to food (process fortification) can be undertaken by the food industry. If selenomethionine is added directly to food, however, oxidation due to heat processing needs to be avoided. New ways to biofortify food products are needed, and it is generally observed that there is less wastage if selenium is added late in the production chain rather than early. On these bases we have proposed adding selenium-enriched, sprouted cereal grain during food processing as an efficient way to introduce this nutrient into deficient diets. Selenium is a non-renewable resource. There is now an enormous wastage of selenium associated with large-scale mining and industrial processing. We recommend that this must be changed and that much of the selenium that is extracted should be stockpiled for use as a nutrient by future generations

Variation in grain Zn concentration, and the grain ionome, in field-grown Indian wheat

Wheat is an important dietary source of zinc (Zn) and other mineral elements in many countries. Dietary Zn deficiency is widespread, especially in developing countries, and breeding (genetic biofortification) through the HarvestPlus programme has recently started to deliver new wheat varieties to help alleviate this problem in South Asia. To better understand the potential of wheat to alleviate dietary Zn deficiency, this study aimed to characterise the baseline effects of genotype (G), site (E), and genotype by site interactions (GxE) on grain Zn concentration under a wide range of soil conditions in India. Field experiments were conducted on a diverse panel of 36 Indian-adapted wheat genotypes, grown on a range of soil types (pH range 4.5–9.5), in 2013–14 (five sites) and 2014–15 (six sites). Grain samples were analysed using inductively coupled plasma-mass spectrometry (ICP-MS). The mean grain Zn concentration of the genotypes ranged from 24.9–34.8 mg kg-1, averaged across site and year. Genotype and site effects were associated with 10% and 6% of the overall variation in grain Zn concentration, respectively. Whilst G x E interaction effects were evident across the panel, some genotypes had consistent rankings between sites and years. Grain Zn concentration correlated positively with grain concentrations of iron (Fe), sulphur (S), and eight other elements, but did not correlate negatively with grain yield, i.e. no yield dilution was observed. Despite a relatively small contribution of genotype to the overall variation in grain Zn concentration, due to experiments being conducted across many contrasting sites and two years, our data are consistent with reports that biofortifying wheat through breeding is likely to be effective at scale given that some genotypes performed consistently across diverse soil types. Notably, all soils in this study were probably Zn deficient and interactions between wheat genotypes and soil Zn availability/management (e.g. the use of Zn-containing fertilisers) need to be better-understood to improve Zn supply in food systems

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Results of a phase IIa clinical trial of an anti-inflammatory molecule, chaperonin 10, in multiple sclerosis

BackgroundChaperonin 10 (Cpn10) is a mitochondrial molecule involved in protein folding. The aim of this study was to determine the safety profile of Cpn10 in patients with multiple sclerosis (MS).MethodsA total of 50 patients with relapse-remitting or secondary progressive MS were intravenously administered 5 mg or 10 mg of Cpn10 weekly for 12 weeks in a double-blind, randomized, placebo controlled, phase II trial. Clinical reviews, including Expanded Disability Status Scale and magnetic resonance imaging (MRI) with Gadolinium, were undertaken every 4 weeks. Stimulation of patient peripheral blood mononuclear cells with lipopolysaccharide ex vivo was used to measure the in vivo activity of Cpn10.ResultsNo significant differences in the frequency of adverse events were seen between treatment and placebo arms. Leukocytes from both groups of Cpn10-treated patients produced significantly lower levels of critical proinflammatory cytokines. A trend toward improvement in new Gadolinium-enhancing lesions on MRI was observed, but this difference was not statistically significant. No differences in clinical outcome measures were seen.ConclusionsCpn10 is safe and well tolerated when administered to patients with MS for 3 months, however, a further extended phase II study primarily focused on efficacy is warranted.SA Broadley, D Vanags, B Williams, B Johnson, D Feeney, L Griffiths, S Shakib, G Brown, A Coulthard, P Mullins and C Kneebon