Dr Almeida received during the project training from Prof. Ian Nabney, and other colleagues at Aston addressing various topics, such as: project management, IP, technical writing, open access and research data management, as well as career and personal development planning. She successfully completed Introduction to Learning and Teaching Practises (ILTP) course and Postgraduate Certificate in Learning &Teaching in Higher Education (PGCert).
The Fellow collaborated with The Royal Orthopaedic Hospital during a clinical secondment that provided the essential clinical training, namely training in the assessment, measurement and monitoring of vital signs and mandatory training sessions (including infection control, information governance and data protection, dignified treatment of patients, health and safety).
Dr Almeida also participated in dissemination activities through Aston’s Marie Curie Fellowship blog (
http://www.mariecurie.astonblogs.co.uk/category/vania-almeida/(si apre in una nuova finestra)) where she wrote posts about her own experience as Marie Curie Fellow, outreach activities and its impact on general public, the importance of a well-balanced training program to achieve a position of professional maturity, and how to prepare a career development program.
The Fellow’s training needs were addressed through a personal Career Development Plan aimed at diversifying and complementing her research skills and knowledge, providing her with a range of special technical training in the area of machine learning techniques and in the assessment, measurement and monitoring of vital signs in medical environment.
A wireless system was implemented in a clinical ward at The Royal Orthopaedics Hospital NHS Trust in collaboration with Sensium Healthcare Ltd. In the first year, all the clinical approvals were obtained, from the NHS Research Ethics Committee (REC)/ Health Research Authority (HRA), and NIHR Clinical Research Network. A data management plan was also designed to recruit two groups of subjects: knee or hip replacement patients (revision patients) and clinical staff on the wards that care for adult patients who undergone joint or spinal surgery. The recruitment ended on 30 September and 202 participants were recruited.
The data collected in this study included vital signs, information on the patients’ care, wellbeing and pain levels, and the experience of patients with wireless vital sign monitoring. A second study, a hospital-wide survey was carried out with patients and staff from joint and spinal surgery wards. These tasks were added to the original plan aiming to improve the clinical impact of this study, contributing to a better understanding of the patients’ needs, and to provide additional information about patient feedback to the clinical and industrial partners.
Dr. Vania Almeida studied potential indicators of physiological deterioration by the analysis of vital-sign tipping points. The first results were achieved using a dataset comprising heart rate (HR) time series. Different indicators were considered: 1) generic early warning indicators used in ecosystems analysis (autocorrelation at-1-lag (ACF1), standard deviation (SD), skewness, kurtosis and heteroskedasticity) and 2) entropy analysis (kernel entropy and multi scale entropy). The results were published in the IEEE EMBC 2016 in Orlando, Florida, USA.
In another study the objective was to quantify the potential bias of switching models in the presence of non-stationarities, when the inputs are spectral, symbolic and entropy indices. To distinguish stationary from non-stationary periods, a test was used to verify the stability of the mean and variance over short periods. The results were published in the IEEE EMBC 2017 in Jeju, South Korea.
Dr. Almeida continues to collaborate with Aston University as a Visiting Lecturer, and she is currently preparing further papers to be submitted over the next year focusing on the data collected during the project.
