Research Focus

In many neurological disorders patients are suffering from impaired gait and mobility. Current clinical routine visits can usually not reflect the daily life health status of patients. For more objective observations we attach inertial measurement units (IMUs) to the patients’ shoes or lower back and obtain motion measurements over several days and weeks. My tasks relate to the analysis of the sensor raw data and the extraction of useful clinical information by developing algorithms and software. These can range from the counting of steps per day up to the estimation and prediction of fall risk. The ultimate goal of my research is to make the job of doctors easier and support patients with their disease.

• Algorithms for long-term, real-life gait analysis, especially of patients with Parkinson’s disease
  
• Machine-learning based estimation and prediction of fall risk