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About me

MSc in electrical engineering 1975 at Chalmers University of Technology in Gothenburg, returned to Chalmers as PhD candidate after two years at Ericsson in Mölndal. Graduated as PhD in Applied Electronics in 1983 on a thesis about micro processor based signal processing of fetal-EKG. 1983-2001 different half time research and teaching positions at Chalmers combined with a half time position at Stiftelsen Medicin & Teknik (Foundation for Biomedical Engineering), from 1987 as CEO. Associate professor in Medical Electronics at Chalmers 1989, declared competent for professorship in Medical Signal Processing by Technical University of Denmark 1995. 2001-2009 professor in Medical Signal Processing and Systems Engineering, University of Borås, and 2005-2006 acting pro rector responsible for research. Since 2010 professor i Medical Technology at School for Technology and Health at KTH, Royal Institute of Technology, Stockholm, affiliated to till Department of Clinical Science, Intervention and Technology, at Karolinska institutet.

Education

Teaching interest
Years of teaching in subjects related to electrical and biomedical engineering, eg. Electronic circuits, Analogue and Digital Signal Processing, Physiological Measurements at Chalmers in Gothenburg and at University of Borås. Responsible for the development and running of several master programs, such as Health Care Informatics at the IT University in Gothenburg, Biomedical Engineering University of Borås.

Research description

Research interest
A common theme for the research is the use of a tool box of measurement technology and systems engineering paired with signal processing and modelling methods to solve relevant clinical problems. Typically one or several physiological signals are recorded, the information in the signals is extracted and some decision support may be provided. Following are some current examples:

Cerebral monitoring of neonates
The past 20 years has seen a dramatic increase in survival rates of premature babies. In Sweden today, an additional 500 very immature and low birth weight babies survive each year compared to 20 years ago. These babies are 100 times more likely to sustain neurological damage after birth than term infants. A challenge for neonatology is now to improve the chances for intact survival. If at-risk infants could be continuously monitored for the onset of threatening events, the risk of neurological damage can be minimised or prevented with new treatments. Today no such monitoring is routinely available. Continuous monitoring of the EEG can provide information for this purpose, but hospitals lack the facilities to do so. Not all neonatal EEG changes have been fully investigated or are fully understood. To address this, clinical and experimental studies have been started. Clinical and experimental results are now becoming available and provide an ideal opportunity to perform a detailed exploration of this data using modern engineering techniques.

The current project uses novel and existing signal processing and analysis techniques to analyse and classify patterns that can be extracted from the EEG to detect the onset of the adverse neurological events. This will than serve as tools for the neonatologist for monitoring and detection of adverse neurological events, will allow for proper treatment and also assist in the development of more effective treatment to minimise or prevent brain damage.

Stroke diagnosis
Brain stroke (BS) is the 3rd leading cause of the death in the world and it is the major cause of permanent neurological disability. As many as in 2 out 3 cases of the devastating effects of BS could be prevented with prompt proper treatment. However, available detection methods, based on imaging techniques, do not facilitate early detection. Recently, it has been confirmed that the electrical properties of brain tissue change during ischemia and such change modifies the electrical bioimpedance of the brain. The current project aims at exploring the abilities to utilise electrical bioimpedance as a tool to distinguish between ischemic and hemorrhagic stroke.

Monitoring of patients with chronic kidney disease
Chronic kidney disease is a severe disease that in often requires replacement therapy, i.e. dialysis or kidney transplantation. The prevalence of CKD has now reached epidemic proportions with 10-12% of the population showing signs of CKD and it could thus be regarded as a public health priority.

Dialysis performs the task of removing waste and fluid from the body, and it is sometimes the only treatment capable of maintaining the life of the patient. However, with dialysis some key natural physiological mechanisms for control of hydration and ion balance are lost; dialysis also fails to substitute the endocrine functions of the kidney. This means that it is up to the clinicians to keep these important factors under control, but despite many important technological developments there are still no good tools for assessment of hydration. The project aims at using electrical bioimpedance (EBI) techniques to address and solve the problem. Various aspects EBI have been studied for many years but to date no good methodology for assessment of body liquid content and distribution has been established in clinical routine.

Many CKD patients also suffer from inflammatory disease resulting in poor autonomous control. The project also aims at using analysis of heart rate variability HRV to detect and monitor the function of the autonomous nervous system.

Care@Distance home monitoring of elderly and chronically ill patients
Care@Distance is a project aimed at monitoring patients conditions in their own homes on a daily basis in order to catch early signs of deterioration in health status. With such monitoring it ought to be possible to avoid acute situations, increase treatment compliance, and improve disease management.

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