A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors

We present a novel framework to monitor the three- dimensional trajectory (orientation and position) of a golf swing using miniaturized inertial sensors. Firstly we employed a highly accurate and computationally efficient revised gradient descent algorithm to obtain the orientation of a golf club. Secondly, we designed a series of digital filters to determine the backward and forward segments of the swing, enabling us to calculate drift-free linear velocity along with the relative 3D position of the golf club during the entire swing. Finally, the calculated motion trajectory was verified against a ground truth VICON system using Iterative Closest Point (ICP) in conjunction with Principal Component Analysis (PCA). The computationally efficient framework present here achieves a high level of accuracy (r = 0.9885, p < 0.0001) for such a low-cost system. This framework can be utilized for reliable movement technique evaluation and can provide near real-time feedback for athletes in various unconstrained environments. It is envisaged that the proposed framework is applicable to other racket based sports (e.g. tennis, cricket and hurling)

The effects of small-scale impoundments and bank reinforcing on fish habitat and composition in semi-natural streams

We studied the fish assemblages of thirty one, 2(nd)-4(th) order "least- impacted" streams with a varying degree of low-level management in central Portugal, using a standardised survey to document the river habitat. Channel, banks and riparian landuse, described separately according to principal component scores, were significantly related to altitude, slope and management intervention. Species diversity was low, represented by four endemic, four pan-European and one exotic species. TWINSPAN classification distinguished 3 community types, characterised by their dominant species: trout (Salmo trutta L.), chub (Leuciscus carolitertii Doadrio) and "roach" (Squalius alburnoides Steindachner and Chondrostoma oligolepis Robalo). Community types were associated with environmental differences with PC Channel scores higher at trout sites compared to other classification groups, whilst PC Bank-1 scores, temperature and conductivity were significantly different at trout compared to "roach" sites. Ecologically important habitat features were, in turn, related to landscape (map-derived) parameters and the extent of channel and bank management. The mis-classification of sites in discriminant analysis was related to management intervention, indicating the potential difficulty in the assignment river-community types for the biological monitoring of fish communities in these stream types.FCT/MCTE

Kinect vs. low-cost inertial sensing For gesture recognition

In this paper, we investigate efficient recognition of human gestures / movements from multimedia and multimodal data, including the Microsoft Kinect and translational and rotational acceleration and velocity from wearable inertial sensors. We firstly present a system that automatically classifies a large range of activities (17 different gestures) using a random forest decision tree. Our system can achieve near real time recognition by appropriately selecting the sensors that led to the greatest contributing factor for a particular task. Features extracted from multimodal sensor data were used to train and evaluate a customized classifier. This novel technique is capable of successfully classifying var- ious gestures with up to 91 % overall accuracy on a publicly available data set. Secondly we investigate a wide range of different motion capture modalities and compare their results in terms of gesture recognition accu- racy using our proposed approach. We conclude that gesture recognition can be effectively performed by considering an approach that overcomes many of the limitations associated with the Kinect and potentially paves the way for low-cost gesture recognition in unconstrained environments

MedFit: The development of a mobile-application to enhance participant self-management of their cardiovascular disease

Background: Cardiovascular disease (CVD) is the leading cause of premature death and disability in Europe. Cardiac Rehabilitation (CR) can reduce the impact of CVD by lowering mortality and morbidity rates and promoting healthy active lifestyles. Yet adherence within CR is low. Research suggests that mHealth interventions are useful in supporting the self-management of chronic disease. The purpose of this research is to report on the development of an mHealth intervention. Methods: For the intervention development the Medical Research Council’s formative process consisting of 4 stages; i) development, ii) feasibility/piloting, iii) evaluation and iv) implementation will be used to develop a theoretically informed Android App to enhance disease self-management and quality of life in CVD. Like CR it will use exercise as its main modality, and provide advice on other health behaviours. Results: A systematic review of the use of behaviour change techniques (BCTs) in physical activity eHealth interventions for CVD patients has been conducted. Seven electronic databases yielded 987 articles, 97 of which met the inclusion criteria for full text review. A multidisciplinary team comprised of exercise scientists, health behaviour change and technology specialists are using this information to develop the intervention prototype. Stage one will be followed by qualitative research, where end-users will be asked to examine the intervention in order to determine its feasibility and acceptability, to ultimately improve its efficacy through a co-design process. Conclusion: Preliminary findings and systematic review protocol will be reported as per the PRISMA guidelines, ultimately aiding the development of the MedFit app

Technology use among patients with cardiovascular disease: an assessment of patient need for a technology enabled behavioural change intervention.

Effective Cardiac Rehabilitation (CR) can significantly improve mortality and morbidity rates in relation to cardiovascular disease; however, uptake of traditional community-based long-term is very low. PATHway (Physical Activity Towards Health) will provide individualized rehabilitation programs, through an internet-enabled sensor-based home exercise platform that allows remote participation. The purpose of this study was to assess the level of interest and use of technology by individuals living with CVD in order to inform the design of a technology-enabled CR programme. Method: A technology usage questionnaire based on a previous study investigating the role of technology and mHealth in a CVD population was used (Dale et al., 2014) to ascertain the current level of technology use. All patients attending the Phase Four community cardiac rehabilitation HeartSmart programme (MedEx) were recruited (N=67; 66.2 years, SD= 8.55, Males =76.1%, Females=20.9%). Results: Technology usage was high with 60% of participants owning a smartphone and 85% accessing the internet (54% of whom access it everyday). Participants endorsed the idea of technology enabled cardiac rehabilitation, indicating that they found the idea ‘ appealing’. 79% were interested in receiving ongoing CR support via their smartphones, 79% were interested in receiving CR via the internet. It was found that 52% of patients found the idea of a virtual rehabilitation class appealing. Conclusion: This study provides support for the patient need for a technology enabled behavioural change intervention, specifically through the provision of an internet-enabled sensor-based home exercise platform that allows remote participation in CR exercise programs

A technology platform for enabling behavioural change as a “PATHway” towards better self-management of CVD

We describe a technology platform developed as part of a novel approach to technology-enabled exercise-based Cardiac Rehabilitation (CR), termed PATHway. We explain the overall concept and explain how technology can facilitate remote participation and better adherence to communitybased long-term Phase III CR. The demo will showcase the user experience of interacting with the PATHway system, including navigation and manual data entry, whilst also demonstrating real-time sensing and analysis of exercise movements and automatic adaptation of exercise based on physiological response

Mathematics education and technology

Recent international surveys such as the Organisation for Economic Co-operation and Development (OECD) report Students, Computers and Learning ( 2015) highlight the wide gap in students’ access to, and use of, technology in secondary mathematics in participating countries. The OECD “snapshot” methodology in which 15-year-old students were asked if they (or their teachers) had performed a range of mathematical tasks using computers in the month preceding their completion of the Programme for International Student Assessment (PISA) survey revealed low levels of technology use (see Fig. 1)

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Four Reasons to Question the Accuracy of a Biotic Index; the Risk of Metric Bias and the Scope to Improve Accuracy

<div><p>Natural ecological variability and analytical design can bias the derived value of a biotic index through the variable influence of indicator body-size, abundance, richness, and ascribed tolerance scores. Descriptive statistics highlight this risk for 26 aquatic indicator systems; detailed analysis is provided for contrasting weighted-average indices applying the example of the BMWP, which has the best supporting data. Differences in body size between taxa from respective tolerance classes is a common feature of indicator systems; in some it represents a trend ranging from comparatively small pollution tolerant to larger intolerant organisms. Under this scenario, the propensity to collect a greater proportion of smaller organisms is associated with negative bias however, positive bias may occur when equipment (e.g. mesh-size) selectively samples larger organisms. Biotic indices are often derived from systems where indicator taxa are unevenly distributed along the gradient of tolerance classes. Such skews in indicator richness can distort index values in the direction of taxonomically rich indicator classes with the subsequent degree of bias related to the treatment of abundance data. The misclassification of indicator taxa causes bias that varies with the magnitude of the misclassification, the relative abundance of misclassified taxa and the treatment of abundance data. These artifacts of assessment design can compromise the ability to monitor biological quality. The statistical treatment of abundance data and the manipulation of indicator assignment and class richness can be used to improve index accuracy. While advances in methods of data collection (i.e. DNA barcoding) may facilitate improvement, the scope to reduce systematic bias is ultimately limited to a strategy of optimal compromise. The shortfall in accuracy must be addressed by statistical pragmatism. At any particular site, the net bias is a probabilistic function of the sample data, resulting in an error variance around an average deviation. Following standardized protocols and assigning precise reference conditions, the error variance of their comparative ratio (test-site:reference) can be measured and used to estimate the accuracy of the resultant assessment.</p></div

The unimodal probability distribution applied to indicator selection in simulation models illustrating two generalized examples.

<p>a). A symmetric distribution ranging across 7 indicator classes that occurs for mid-range scores defined by probabilities = 0.05,0.10,0.20,0.30,0.2,0.1,0.05. b). A truncated distribution that occurs for end-group scores, in this case associated with a mode of 10 where the “missing” probabilities, totaling 0.35 (i.e., the right-hand probabilities = 0.20,0.10,0.05, respectively corresponding to the non-defined indicator ranks of 11,12,13) are divided in proportion of the indicator ranks present (giving truncation-adjusted probabilities = 0.8,0.15,0.31,0.46).</p