A5069821903- Cardiac Health and Mental Health
- Peripheral Artery Disease Management
- Heart Rate Variability and Autonomic Control
- Cardiovascular and exercise physiology
- Stroke Rehabilitation and Recovery
- Electronic Health Records Systems
- Medication Adherence and Compliance
- Text Readability and Simplification
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Biomedical Text Mining and Ontologies
- Machine Learning in Healthcare
- Chronic Disease Management Strategies
- Sleep and Work-Related Fatigue
- Data Quality and Management
- Digital Mental Health Interventions
- Time Series Analysis and Forecasting
- Diagnosis and Treatment of Venous Diseases
- Artificial Intelligence in Healthcare
- Healthcare Systems and Technology
- Musculoskeletal pain and rehabilitation
- Sleep and related disorders
- Cardiovascular Health and Disease Prevention
- Health Literacy and Information Accessibility
- EEG and Brain-Computer Interfaces
- Hemodynamic Monitoring and Therapy
Austrian Institute of Technology
2021-2025
Graz University of Technology
2023-2024
Austrian Institute for Health Technology Assessment GmbH
2023-2024
Ludwig Boltzmann Gesellschaft
2024
Digital Health Cooperative Research Centre
2024
FH JOANNEUM University of Applied Sciences
2021-2024
Fachhochschule Wiener Neustadt
2023
: Guidelines recommend walking trainings for peripheral arterial disease (PAD) management. Supervised training is superior to advise improve the distance. Telehealth service with nurse support may close this gap.
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with severe complications such as ischemic stroke and heart failure. Early detection essential for timely intervention; however, traditional diagnostic methods often lack scalability accessibility. This project explores the use of photoplethysmography (PPG) signals recorded via smartphone applications to develop predictive neural network model AF detection. Data collection involved student participants using app,...
Introduction The potential for secondary use of health data to improve healthcare is currently not fully exploited. Health largely kept in isolated silos and key infrastructure aggregate these into standardized bodies knowledge underdeveloped. We describe the development, implementation, evaluation a federated facilitate versatile based on Data Space nodes. Materials methods Our proposed nodes are self-contained units that digest through an extract-transform-load framework pseudonymizes...
Background: The recent rise of large language models has triggered renewed interest in medical free text data, which holds critical information about patients and diseases. However, is also highly sensitive. Therefore, de-identification typically required but complicated since mostly unstructured. With the Masketeer algorithm, we present an effective tool to de-identify German text. Methods: We used ensemble different masking classes remove references identifiable data from over 35,000...
Clinical notes provide valuable data in telemonitoring systems for disease management. Such must be converted into structured information to effective automated analysis. One way achieve this is by classification (e.g. categories). However, conform with privacy regulations and concerns, text usually de-identified.This study investigated the effects of de-identification on classification.Two pseudonymisation two algorithms were applied clinical messages from a telehealth system. Divergence...
Cardiovascular diseases are the leading cause of death worldwide and partly caused by modifiable risk factors. Cardiac rehabilitation addresses several these factors, such as physical inactivity reduced exercise capacity. However, despite its proven short-term merits, long-term adherence to healthy lifestyle changes is disappointing. With regards training, it has been shown that supplemented a) home-based training b) supportive digital tools can improve adherence.In our multi-center study...
Telehealth services are becoming more and popular, leading to an increasing amount of data be monitored by health professionals. Machine learning can support them in managing these data. Therefore, the right machine algorithms need applied We have implemented validated different for selecting optimal time instances from series derived a diabetes telehealth service. Intrinsic, supervised, unsupervised instance selection were analysed. Instance had huge impact on accuracy our random forest...
<sec> <title>BACKGROUND</title> Telehealth has been effective in managing cardiovascular diseases like stroke and heart failure shown promising results patients with peripheral arterial disease (PAD). However, more work is needed to fully understand the effect of telehealth based predictive modelling on physical fitness PAD patients. </sec> <title>OBJECTIVE</title> For this work, from Keep Pace study were analyzed depth gain insights temporal developments patients’ conditions develop models...
Telehealth has been effective in managing cardiovascular diseases like stroke and heart failure shown promising results patients with peripheral arterial disease. However, more work is needed to fully understand the effect of telehealth-based predictive modeling on physical fitness For this work, data from Keep Pace study were analyzed depth gain insights temporal developments patients' conditions develop models predict total walking distance at end. This could help determine who are likely...
Heart failure is a common chronic disease which associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care management program HerzMobil, monitoring data such as daily measured vital parameters various other heart related are collected in structured way. Additionally, involved healthcare professionals communicate one another via system using free-text clinical notes. Since manual annotation of notes too time-consuming for routine...
<sec> <title>BACKGROUND</title> Home and telehealth-based interventions are increasingly used in cardiac rehabilitation (CR), a multidisciplinary model of health care. Digital tools such as wearables or digital training diaries expected to support patients adhere recommended lifestyle changes, including physical exercise programmes. As previously published, the EPICURE study analysed effects tools, i.e., diary, adherence monitoring, wearables, on capacity during out-patient CR phase III...
Background: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics 18 participants over four weeks, including heart rate, physical activity, and both device-measured self-reported quality. Objectives: The primary objective was correlate device with subjective perceptions. Methods: Our approach used processing, feature engineering, optimizing Multi-Layer Perceptron...
Peripheral artery disease (PAD) is a widespread condition affecting over 200 million people worldwide. PAD leads to restricted blood flow the extremities, causing painful limitations and risk of amputation in advanced stages. Among medical surgical interventions, therapy involves walking training. Two commonly used standardized tests measure performance general mobility are 6-minute walk test (6MWT) timed-up-and-go (TUG) test. Since 6MWT takes more time effort complete than TUG test,...
Home and telehealth-based interventions are increasingly used in cardiac rehabilitation, a multidisciplinary model of health care. Digital tools such as wearables or digital training diaries expected to support patients adhere recommended lifestyle changes, including physical exercise programs. As previously published, the EPICURE study (effect outpatient rehabilitation home training) analyzed effects tools, that is, diary, adherence monitoring, wearables, on capacity during phase III...
The aging population's need for treatment of chronic diseases is exhibiting a marked increase in urgency, with heart failure being one the most severe this regard. To improve outpatient care these patients and reduce hospitalization rates, telemedical disease management program HerzMobil was developed past.This work aims to analyze inter-annotator variability among two professional groups (healthcare engineering) involved program's annotation process free-text clinical notes using...
The 6-Minute Walk Test (6-MWT) is frequently used to evaluate functional physical capacity of patients with cardiovascular diseases. To determine reliability in remote care, outlier classification a mobile Global Navigation Satellite System (GNSS) based 6-MWT App had be investigated. raw data 53 measurements were Kalman filtered and afterwards layered Butterworth high-pass filter find correlation between the resulting Root Mean Square value (RMS) outliers relative walking distance errors...