14:00 Welcome Address & Moderation
Jakob Doppler, Program Director for Digital Healthcare, St. Pölten University of Applied Sciences
Jürgen Pripfl, Director for Center for Digital Health Innovation, St. Pölten University of Applied Sciences
14:15 Keynote – A European Perspective on the Estonian eHealth Setup
Peeter Ross, Program Director for Health Care Technology, Tallinn University of Technology
Estonia is one of the world leaders in the provision of public digital services. The national web-based communications and transactions platform provides modern and safe governance by allowing for transparency, security, privacy, entrepreneurship and, among other things, trusted way to exchange health data between health care professionals and citizen. The eHealth system integrates different health care databases and services. It makes possible to access medical data and services, prescriptions and images in a secure way. The objective of this presentation is to give an overview of the design and implementation of Estonian nation-wide eHealth system, its outcomes and its future perspectives.
14:45 Automated Assessment of Human Gait By Artificial Intelligence Methods
Matthias Zeppelzauer, Senior Researcher, St. Pölten University of Applied Sciences
A rising number of people in our community, particularly elderly adults, suffer from gait deficits. To identify the underlying cause and to determine appropriate therapy procedures clinics and rehabilitation centers employ force plates along with cost-effective two-dimensional gait analysis tools to determine kinematic and kinetic gait variables. These data help to assess patient gait disorders and to monitor patient progress during physical therapy treatment. However, current gait analysis relies heavily on visual inspection of the associated signals. This subsequently leads to subjective and non-repeatable assessments and is a task, which requires substantial clinical experience and is thus expensive. We investigate machine learning and deep learning methods for the automated assessment of gait and gait deficits. Based on a large-scale database of real-world gait patterns we design powerful statistical models for the detection and classification of gait deficits. Our methods enable novel ways to obtain objective, repeatable, and low-cost assessments and thus represent a valuable tool to support physical therapists in clinical decisions in future.
15:00 Data Visualization for Analyzability of Flow Cytometry Data related to Pediatric Stem Cell Transplantation
Jakob Winkler, Application Specialist, Sanitas GmbH
René Geyeregger, Senior Researcher St. Anna Kinderkrebsforschung CCRI – Children’s Cancer Research Institute
Flow cytometry is a commonly used technique to analyze different cell types of human blood cells by their specific surface characteristics. Furthermore, it is used to monitor cell development (engraftment) after allogenic stem cell transplantation (allo-HSCT). These analyses have been performed at the St. Anna Children’s Cancer Research Institute since 1995, but the data have been recorded in a slightly unstructured way in separate Excel tables. This session describes the results of data scraping of 26462 historical data sets (1995 – 2016) and visualizing them in interactive, web-based charts. Amongst other results, this undertaking revealed interesting trends of correlation between donors’ / recipients’ age and cell counts of naïve CD4+ T-cells. The results will lead to improved analyzability of patients undergoing hematopoietic stem cell transplantation at the St. Anna Children’s Hospital.
15:30 Challenges in the Development of a Diagnosis and Decision Support App for Physicians
Michael Mikesch, COO, Diagnosia
Diagnosia develops a modern drug information suite which supports medical professionals. In this session, we will showcase lessons learned from the design and implementation of a decision support service for physicians and highlight technical and functional challenges ahead. Diagnosia increases the efficiency of eMedication and features a speech interface to supports key opinion leaders in a faster clinical decision process.
15:45 Pitch Presentations of Student Projects (10 min each)
- eHealth Wallet – Decentralized EHR Storage And Fast Lane Hospital Admission
Gerald Wagner, Julia Möseler
+ Team: Christopher Csenar, Doris Kraushofer, Tatjana Zimmermann
The aim of this project is to close the still existing digital gap between pre-clinical examinations and hospital admission. Human capacities and a huge amount of money are wasted due to inefficient hospital admission processes. By establishing a new way of how personal health data can be collected and transferred from the patient to the HIS, there will be advantages for all involved stakeholders. The user keeps their medical data on their own device – so all relevant health data of the patient is stored in a single place. There will be no synchronization of any data via the internet. eHealth Wallet stores locally and transfers only user defined data to the healthcare providers. Time for hospital admission can be reduced, patients do not need to carry lots of printed material and data is transferred securely.
- Chin-Up – Solution for the “Smartphone Neck”
Sophia Hannah Widmann, Thomas Illetschko
+ Team: Anna Hain, Isabel Nicole King, Sophie-Catherine Schilling
Smartphones and mobile devices are increasingly present in our daily life. With the constant growth in mobile user populations all over the world, new health conditions are emerging; so-called “digital diseases”. Looking down at a smartphone or mobile device for extended periods might lead to posture problems, also known as “text neck” or “smartphone neck”. The aim is to raise awareness of poor posture and negative effects of excessive mobile phone usage among young people, because nowadays the usage of mobile devices is a common activity and counts as a daily routine. A long-term goal is to prevent poor cervical spine posture and to improve the head alignment. Our application should help young adults to improve phone usage patterns.
- Sm@rt Work – Healthier Work & Life at a Construction Site
Max Valentin Jesenko, Niklas Paul Stockreiter
+ Team: Bernhard Ruhrhofer, Bogdan-Alin Negrei, Eva Maria Kamper, Florian Schweifer, Katharina Maier
Every day, construction workers are exposed to work-related physical and mental stress. Lifting and carrying heavy loads paired with noise pollution, mental stress and other factors have a negative impact on construction workers’ health. Possible consequences are shoulder-, neck- and back pain or sleeping disorders, to name a few. Sm@rt Work is an application that checks the status of your personal health literacy via questionnaires. It provides further steps and actions to improve your workflow and personal health. Our goal is to strengthen the health literacy of STRABAG construction workers and to contribute to a healthier lifestyle, less injuries, better work capacity and therefore reduced costs for the employer.
- Smart Brain – Intelligent Personal Assistants for F.A.S.Ter Stroke Detection
Markus Bertl, Susanna Weißenböck
+ Team: Eduard Kessler, Melanie Griesser, Teresa Nepras
Smart voice assistants like Amazon Alexa become increasingly important in everyday life, especially when thinking of service ideas in the context of health promotion and advice. Besides technical difficulties such as incomplete human computer interaction metaphors and poor usability, ethical and data protection issues (even with healthy users) need to be discussed. This talk presents a prototypical approach of a speech interface for the F.A.S.T stroke detection test.
- Nutrition eTherapy – Remote Nutrition Monitoring System for Oncology Patients
Elise Margaret Mandl, Georg Hofstätter
+ Team: Christian Waldschütz
Cancer patients, especially in extramural, care face a high risk of malnutrition. Research shows that therapy can improve patient outcomes but is often fragmented which can impede continuous and personal communication. Nutrition eTherapy is a prototypical mobile and and web based solution for nutritional remote monitoring that tries to bridge the gap between clinical and commercial interests and more importantly empowers the patient. Real time analysis of data entered allows early detection of malnutrition and timely communication with healthcare providers. This promotes improved quality of life for both patients and their carers/relatives. Future enhancements could integrate chat bots, therapy diaries and sensor connectivity.