Research Group Biosignal Analysis & Digital Health
Sensors play an important role in the digitization of healthcare: smartwatches measure vital signs and count steps to motivate people to get fit every day. The heart and brain are monitored in the clinic using electrical signals.
In our specialist group "Biosignal Analysis & Digital Health", we focus on the entire value chain in the area of sensors, data and health. The appropriate interaction of technology, organization and people is central to success. One promising topic, for example, is patient monitoring in hospitals using wristbands that measure the most important vital signs. Targeted, early warning signals can offer decisive added value in the often resource-strained situations. For this to succeed, the sensor technology and data analysis must first be tailored to the clinical context. Algorithms and artificial intelligence are often used here. Equally relevant is the appropriate design of the technology in relation to organizational processes and the needs of the specialists. The best algorithm is of no use if the automatically generated warning does not reach the appropriate recipient at the right time! Here we commit ourselves to the philosophy of "Human-Centered Design" to guarantee the maximum benefit of the technology. Accordingly, the research group feels committed to both topics: Biosignal Analysis & Digital Health.
- Sensor technology and physics: wearables, EEG, ECG, acoustics
- IoT: data acquisition, connectivity, databases, cloud
- Sensor data and time series analysis
- Signal processing, algorithms and machine learning
- Application for application-oriented funding (Innosuisse, DIZH, etc.)
- Design of studies with sensor technology under the framework of data protection and ethics
- Interdisciplinary project management (clinical, technical, private)
- Usability and Human-Centered Design
Biosignals in the clinical setting
- Patient monitoring using wearables
- Analysis of EEG and ECG data
- Patient reported outcomes
Biosignals in private context
- Wearable technology for well-being, mental health, etc.
- Non-clinical applications of neurofeedbacl (Ex: openbci)
- Health applications around smartphones (ex: acoustic biosignals)
Applied projects in health are usually interdisciplinary: Typically, we work simultaneously with clinical partners and private companies to bring technology into use in an economical and user centerd way. Thanks to our broad network in the ZHAW Digital Health Lab with clinics, private companies and other research partners, we can organize and lead suitable project constellations.
Our research area includes teaching activities at BSc and MSc level.
Examples of project work:
- Algorithm for predicting complications using vital signs
- Automatic data quality verification in clinical trials