Biomedical signal analysis

Individualised healthcare is a recent global megatrend aiming to improve health and wellbeing. We are developing breakthrough technologies to tackle key challenges including next generation signal analysis techniques towards personalized medicine and wellness solutions.

The mission of the Physiological Signal Analysis Team is to carry out top-level basic, applied and translational research in biomedical engineering. The aim is to develop, apply and evaluate novel biomedical measurement technologies in health and wellbeing. The research focuses on measurement of physiological phenomena associated with:
  • cardiovascular system
  • respiratory system
  • central nervous system and autonomic nervous system
  • affective system / emotions
Our research is multi-disciplinary and is carried out in collaboration with hospitals and industry partners in Finland and abroad. We use large clinical materials for method development and validation. Large-scale cohorts, digital biobanks and other emerging digital repositories of health data are increasingly important data sources for our research.  Our research addresses future e-health systems where big data analytics combined with sensitive health data offers many opportunities but also challenges concerning, for example, privacy and security.
The research profile is based on linking information technology and medicine, with an aim to utilize methodologies of information engineering, signal and image processing, pattern recognition, biophysics, medical imaging, applied mathematics, simulation, biomedicine and clinical medicine.

Cardiorespiratory research

One of our main focus areas is the assessment of autonomic nervous system (ANS) function as it is the most important regulatory system in the human body controlling vital functions and homeostasis. We are especially interested in respiratory and cardiovascular functions. Over the decades, we have developed a wide array of signal analysis tools for analysing and interpreting related physiological signals such as multi-channel ECG, heart rate, blood pressure and respiratory airflow signals. We are constantly improving and extending the toolbox with state-of-the-art methods. Application domains range from clinical to ambulatory, e.g. from risk stratification and prediction of sudden cardiac death to personalized solutions endorsing increased physical activity and healthy living.

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Neurological research

In our neurological research we tackle challenges emerging in the medical world. Solutions are advancing with the fusion of technical know-how and expertise in physiology. We apply state of the art signal processing solutions for challenges in both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) brain research areas.

We research brain monitoring and brain function assessment with a novel technology, combining EEG measurement and common pharmacological compounds. With intelligent signal analysis, reliable diagnostic information is extracted during anesthesia.

Our fMRI research involves revealing physiological properties of the human brain with novel high temporal resolution recordings. We address both technical and medical challenges to understand the complex resting state properties of the human brain, as well as its connections with external physiological systems, which are notable in blood-oxygen-level dependent (BOLD) signals.

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Digital watermarking, biosecurity & cryptography

The practice of medicine is increasingly evolving towards personalized systems. Development of telemedicine and remote health monitoring is expected to increase cost-effectiveness of healthcare. However, the application of communication technologies leads to various privacy issues. Personal medical information is highly sensitive and needs to be protected against privacy and security threats. Security technologies to counter these threats ranging from cryptography to digital watermarking have been studied by our group.

Digitalization has also entered the health area in a wider sense. Big data collections for research and commercial purposes are increasingly becoming available. Confidentiality of medical data as well as an efficient information management is essential. The team has been working on data management issues of large collections of medical data, their privacy issues and the development of methods for watermarking medical data. We also work on the resilience of hidden information in physical printouts. The topic area – print-cam resiliency - can be considered to be one of the most challenging issues in watermarking images.

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Big data analytics

Digitalization has entered the healthcare area in a wider sense. Big data collections of medical data for research and commercial purposes are increasingly becoming available. For example, new specialized scanners (optical imaging devices) have made it possible to digitize physical medical samples, with a comparable resolution to a traditional microscope.

In biobanks this digitized data along with related clinical and research data forms a cumulative storage of biomedical information, which has an essential role in the future of stratified medicine. This information is valuable both in national and international research initiatives, as well as to commercial purposes.

To allow both internal and external interoperability while maintaining and efficient and secure environment, various information systems must be integrated with other information systems. Due to the sensitive nature of clinical information, privacy and information security play an essential role. In addition, proper anonymization methods needs to be applied whenever data is given out for research purposes.

In healthcare, digitalization creates a possibility for a number of new tools and services to be launched to our aid to perform tasks, such as, quantitative comparison, case sharing and collaboration, as well as computer aided image analysis in digital pathology.

In addition to the before mentioned concepts, big data collections have applications in several other application areas such as sports. Advanced video analysis combined with physiological signal analysis allows us to, i.e., analyze critical incidents, e.g., to improve game tactics and so on. Data visualization techniques can provide a way to more easily comprehend the interactions residing in large collections of data, such as collections of linguistic data.

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Last updated: 22.11.2016