Reducing power and increasing accuracy of on-body sensing in motion capture application.

Motion capture coupled with on-body sensing and biofeedback are key enabling technologies for assisted motor rehabilitation. However, wearability, power efficiency and measurement repeatability remain the principle challenges that need to be addressed before widespread adoption of such systems becomes possible. The weight and the size of the on-body sensing system needs to be kept small, and the system should not interfere with the user's movements or actions, but in general they are bulky due to their power consumption requirements. Furthermore, on-body sensors are very sensitive to positioning, which causes increased variability in the motion data. Isolating the characteristic patterns that represent the most important motion data affected by random positioning errors, while also reducing the power consumption, is the authors' main concern. An automated computational approach is considered to address the two problems. The use of functional principal component analysis is investigated for signal separation, whilst accounting for variability in the sensor position. To generate motion data, movements of human subjects and a robot arm are captured. As joint angles are considered in the analysis, the results are independent from the technology used to measure motion. The proposed post-processing technique can compensate for uncertainties due to sensor positional changes, whilst allowing greater energy efficiency of the sensors, thus enabling improved flexibility and usability of on-body sensing

Comparing Dynamic Hand Rehabilitation Gestures in Leap Motion Using Multi dimensional Dynamic Time Warping

We propose and evaluate the use of Multi-dimensional Dynamic Time Warping (MDTW) for comparing dynamic hand rehabilitation gestures that would be performed by a patient (query) relative to hand gestures prepared by a physiotherapist (reference). MDTW enables us to determine how similar or different a query dynamic hand gesture is to a reference one whilst filtering out unwanted sources of error resulting from positional, rotational or speed differences between the query and the reference actions. It produces a minimum-distance value of a warp path after aligning a query dynamic hand gesture with a reference one. A low minimum-distance value implies the two gestures being compared are similar and high minimum-distance value implies the two gestures vary to a greater extent. When we deliberately compare a specific hand gesture with itself, we obtain a minimum-distance value of 0° indicating the similarity is 100%. Furthermore, when we compare two closely similar hand gestures i.e. gesture 1 and gesture 4, a minimum-distance value of 35.9° is obtained. However, when we compare two quite different gestures i.e. gesture 2 and gesture 3, a minimum-distance value of 248.5° is obtained. Therefore, a physiotherapist can establish whether a patient performs hand rehabilitation gestures satisfactorily or an adjustment is required based on the minimum-distance values of the warp paths

On-body Sensing and Signal Analysis for User Experience Recognition in Human-Machine Interaction

—In this paper, a new algorithm is proposed for recognition of user experience through emotion detection using physiological signals, for application in human-machine interaction. The algorithm recognizes user’s emotion quality and intensity in a two dimensional emotion space continuously. The continuous recognition of the user’s emotion during human-machine interaction will enable the machine to adapt its activity based on the user’s emotion in a real-time manner, thus improving user experience. The emotion model underlying the proposed algorithm is one of the most recent emotion models, which models emotion’s intensity and quality in a continuous two-dimensional space of valance and arousal axes. Using only two physiological signals, which are correlated to the valance and arousal axes of the emotion space, is among the contributions of this paper. Prediction of emotion through physiological signals has the advantage of elimination of social masking and making the prediction more reliable. The key advantage of the proposed algorithm over other algorithms presented to date is the use of the least number of modalities (only two physiological signals) to predict the quality and intensity of emotion continuously in time, and using the most recent widely accepted emotion model

Toward Flexibility in Sensor Placement for Motion Capture Systems: A Signal Processing Approach

Cannot archive published version. Post-Print only. http://www.sherpa.ac.uk/romeo/issn/1530-437X/ Author contacted 21/02/14

Tailoring the Response of Silicon Photonics Devices

Abstract: Shrinking waveguide dimensions in silicon photonics results in a series of performance enhancements, but at some cost. We analyse the waveguide geometry in optical modulators and filters to address some issues associated with this trend. Silicon photonics has experienced rapid development for the last three years and several significant results have been reported, demonstrating the viability of the technology [e.g., 1, 2, 3, 4]. One of the recent trends in silicon photonics has been the reduction of waveguide dimensions. This reduction facilitates tighter bending radii and therefore a smaller device footprint which in turn, significantly reduces the cost. Furthermore, technical performance of many silicon photonic devices is enhanced. However, there are also some issues with this trend to smaller dimensions, notably increased propagation losses, increased polarisation dependence and difficulty in coupling to/from optical fibres. These issues can be overcome with a careful design of the waveguide and device geometry. We have previously shown that by reducing waveguide dimensions, multi-GHz bandwidth optical modulators can be achieved by utilising a horizontal pn junction in a waveguide with an overall height of 450 nm In order to improve the polarisation performance to approach polarisation independence of the modulator, we propose here a modulator with a pn junction that is a V-shape structure, as shown in Highly doped silicon Silicon dioxide Highly doped silicon Highly doped silico

Understanding Public Attitudes and Willingness to Share Commercial Data for Health Research: Survey Study in the United Kingdom

Background: Health research using commercial data is increasing. The evidence on public acceptability and sociodemographic characteristics of individuals willing to share commercial data for health research is scarce. Objective: This survey study investigates the willingness to share commercial data for health research in the United Kingdom with 3 different organizations (government, private, and academic institutions), 5 different data types (internet, shopping, wearable devices, smartphones, and social media), and 10 different invitation methods to recruit participants for research studies with a focus on sociodemographic characteristics and psychological predictors. Methods: We conducted a web-based survey using quota sampling based on age distribution in the United Kingdom in July 2020 (N=1534). Chi-squared tests tested differences by sociodemographic characteristics, and adjusted ordered logistic regressions tested associations with trust, perceived importance of privacy, worry about data misuse and perceived risks, and perceived benefits of data sharing. The results are shown as percentages, adjusted odds ratios, and 95% CIs. Results: Overall, 61.1% (937/1534) of participants were willing to share their data with the government and 61% (936/1534) of participants were willing to share their data with academic research institutions compared with 43.1% (661/1534) who were willing to share their data with private organizations. The willingness to share varied between specific types of data—51.8% (794/1534) for loyalty cards, 35.2% (540/1534) for internet search history, 32% (491/1534) for smartphone data, 31.8% (488/1534) for wearable device data, and 30.4% (467/1534) for social media data. Increasing age was consistently and negatively associated with all the outcomes. Trust was positively associated with willingness to share commercial data, whereas worry about data misuse and the perceived importance of privacy were negatively associated with willingness to share commercial data. The perceived risk of sharing data was positively associated with willingness to share when the participants considered all the specific data types but not with the organizations. The participants favored postal research invitations over digital research invitations. Conclusions: This UK-based survey study shows that willingness to share commercial data for health research varies; however, researchers should focus on effectively communicating their data practices to minimize concerns about data misuse and improve public trust in data science. The results of this study can be further used as a guide to consider methods to improve recruitment strategies in health-related research and to improve response rates and participant retention

European micronutrient recommendations aligned: a general framework developed by EURRECA

Background: In Europe, micronutrient recommendations have been established by (inter)national committees of experts and are used by public health-policy decision makers to monitor and assess the adequacy of the diets of population groups. Current micronutrient recommendations are, however, heterogeneous, whereas the scientific basis for this is not obvious. Alignment of setting micronutrient recommendations is necessary to improve the transparency of the process, the objectivity and reliability of recommendations that are derived by diverse regional and (inter)national bodies. Objective: This call for alignment of micronutrient recommendations is a direct result of the current sociopolitical climate in Europe and uncovers the need for an institutional architecture. There is a need for evidence-based policy making, transparent decision making, stakeholder involvement and alignment of policies across Europe. Results: In this paper, we propose a General Framework that describes the process leading from assessing nutritional requirements to policy applications, based on evidence from science, stakeholder interests and the sociopolitical context. The framework envisions the derivation of nutrient recommendations as scientific methodology, embedded in a policy-making process that also includes consumer issues, and acknowledges the influences of the wider sociopolitical context by distinguishing the principal components of the framework: (a) defining the nutrient requirements for health, (b) setting nutrient recommendations, (c) policy options and (d) policy applications. Conclusion: The General Framework can serve as a basis for a systematic and transparent approach to the development and review of micronutrient requirements in Europe, as well as the decision making of scientific advisory bodies, policy makers and stakeholders involved in this process of assessing, developing and translating these recommendations into public health nutrition policy. European Journal of Clinical Nutrition (201 0) 64, S2-510; doi:10.1038/ejcn.2010.5

Selection and Validation of Reference Genes for Quantitative Real-Time PCR in Buckwheat (Fagopyrum esculentum) Based on Transcriptome Sequence Data

Quantitative reverse transcription PCR (qRT-PCR) is one of the most precise and widely used methods of gene expression analysis. A necessary prerequisite of exact and reliable data is the accurate choice of reference genes. We studied the expression stability of potential reference genes in common buckwheat (Fagopyrum esculentum) in order to find the optimal reference for gene expression analysis in this economically important crop. Recently sequenced buckwheat floral transcriptome was used as source of sequence information. Expression stability of eight candidate reference genes was assessed in different plant structures (leaves and inflorescences at two stages of development and fruits). These genes are the orthologs of Arabidopsis genes identified as stable in a genome-wide survey gene of expression stability and a traditionally used housekeeping gene GAPDH. Three software applications – geNorm, NormFinder and BestKeeper - were used to estimate expression stability and provided congruent results. The orthologs of AT4G33380 (expressed protein of unknown function, Expressed1), AT2G28390 (SAND family protein, SAND) and AT5G46630 (clathrin adapter complex subunit family protein, CACS) are revealed as the most stable. We recommend using the combination of Expressed1, SAND and CACS for the normalization of gene expression data in studies on buckwheat using qRT-PCR. These genes are listed among five the most stably expressed in Arabidopsis that emphasizes utility of the studies on model plants as a framework for other species

Advancing food, nutrition, and health research in Europe by connecting and building research infrastructures in a DISH-RI: Results of the EuroDISH project

Background: Research infrastructures (RIs) are essential to advance research on the relationship between food, nutrition, and health. RIs will facilitate innovation and allow insights at the systems level which are required to design (public health) strategies that will address societal challenges more effectively. Approach: In the EuroDISH project we mapped existing RIs in the food and health area in Europe, identified outstanding needs, and synthesised this into a conceptual design of a pan-European DISH-RI. The DISH model was used to describe and structure the research area: Determinants of food choice, Intake of foods and nutrients, Status and functional markers of nutritional health, and Health and disease risk. Key findings: The need to develop RIs in the food and health domain clearly emerged from the EuroDISH project. It showed the necessity for a unique interdisciplinary and multi-stakeholder RI that overarches the research domains. A DISH-RI should bring services to the research community that facilitate network and community building and provide access to standardised, interoperable, and innovative data and tools. It should fulfil the scientific needs to connect within and between research domains and make use of current initiatives. Added value can also be created by providing services to policy makers and industry, unlocking data and enabling valorisation of research insights in practice through public-private partnerships. The governance of these services (e.g. ownership) and the centralised and distributed activities of the RI itself (e.g. flexibility, innovation) needs to be organised and aligned with the different interests of public and private partners