Join the #P2P2018 & #BeInspired by the experts. 12th May London Heathrow Marriott hotel – Sports Rehab and Education has set an industry standard for sports conferences. From Pain to Performance, held on an annual basis in London in May, is widely recognised as one of the leading sports medicine conferences in the UK.
OActive partner, University of Patras (Visualization and Virtual Reality Group) received the Grand Technical Award, among the twenty teams that participated in the OpenSim Advanced User Workshop that was held at Stanford University during 28-31 March 2018. The paper submitted entitled “Multi-scale analysis of the knee complex” aims to develop multi-scale, patient-specific models of the knee to predict and prevent the progression of osteoarthritis using coupled rigid-body and finite element (FE) analyses. This work is part of the OACTIVE – H2020 project. Some of the project goals are to develop patient-specific knee models in order to assess individuals’ knee mechanics at a tissue level, so that proactive measurements, such augmented reality gait retraining can be made to avoid the progression of OA. For more information visit the following link
24 April 2018, Brussels, Belgium
The open science platform – Frontiers – is organising its second Data Services Workshop in collaboration with the EU Horizon 2020 projects OpenMinTed and OpenUp. This year’s workshop focuses on the application of open research data to support sustainable health initiatives. The event features panelists from leading institutions and companies specializing in this data-driven health research, together with representatives from academic libraries, patient advocacy, research funders, universities and the European Commission.
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The Brussels-based European Alliance for Personalised Medicine (EAPM), sixth annual Presidency conference, which will take place under the auspices of the Bulgarian Presidency of the European Union March 28th 2018, entitled ‘Personalised Medicine and the Big Data Challenge’.
On March 9th and 10th OActive partners AXIA and CETRI met at the AXIA office in Munich, Germany. The discussion focused on the Intellectual Property Rights (IPR) plan of the project and the Data Management Plan (DMP). Data collection protocols were discussed in correlation to the DMP and the documentation of social parameters. Furthermore, the OActive webpage was reviewed and upcoming activities related to the dissemination and exploitation plan were analyzed.
OActive project will be presented at the 56th Congress of the Spanish Society of Rehabilitation and Physical Medicine (Sociedad Española de Rehabilitación y Medicina Física- SERMEF) by the OActive Partners HULAFE on 16-19 May 2018.
After the success of the previous annual meeting in Pamplona, in Cádiz and in Málaga in 2018 the congress will be held in Gijón, Asturia. The Congress covert the scientific fields of neurorehabilitation, skeletal muscle pathology, pain, the relationship with patient associations, management, innovation among others and related to the technical program it will focus on continuous training in intervention, ultrasounds and biomechanics.
The annual OARSI Congress will be held in Liverpool from 26 to 29 April 2018. The annual OARSI Congress is a global forum for those involved in OA research and treatment from academia and industry; including basic scientists, clinical investigators, radiologists, rheumatologists, orthopedic surgeons, physicians in physical medicine and rehabilitation, allied health professionals and policy makers.
Abstract
A novel fuzzy decision tree-based SVM (FDT-SVM) classifier is proposed in this paper, to distinguish between asymptotic (AS) and osteoarthritis (OA) knee gait patterns and to investigate OA severity using 3-D ground reaction force (GRF) measurements. FDT-SVM incorporates effective techniques for feature selection (FS) and class grouping (CG) at each non-leaf nodes of the tree structure, which reduce the overall complexity of DT building and alleviate the overfitting effect. The embedded FS and CG are based on the notion of fuzzy partition vector (FPV) that comprises the fuzzy membership degrees of every pattern in their target classes, serving as a local evaluation metric with respect to patterns. FS is driven by a fuzzy complementary criterion (FuzCoC) which assures that features are iteratively introduced, providing the maximum additional contribution in regard to the information content given by the previously selected features. A novel Wavelet Packet (WP) decomposition based on the FuzCoC principles is also introduced, to distinguish informative and complementary features from GRF data. The quality of our method is validated in terms of statistical metrics drawn by confusion matrices, such as sensitivity, specificity and total classification accuracy. In addition, we investigate the impact of each GRF component. Finally, comparative results with existing techniques are given, demonstrating the efficacy of the suggested approach.
Abstract
Background: Current multimodal approaches for the management of non-specific patellofemoral pain are not optimal, however, targeted intervention for subgroups could improve patient outcomes. This study explores whether subgrouping of non-specific patellofemoral pain patients, using a series of low cost simple clinical tests, is possible.
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