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BACKGROUND Computational state space models (CSSMs) enable the knowledge-based construction of Bayesian filters for recognizing intentions and reconstructing activities of human protagonists in application domains such as smart environments, assisted living, or security. Computational, i. e., algorithmic, representations allow the construction of(More)
Long-term assessment of ambulatory behavior and joint motion are valuable tools for the evaluation of therapy effectiveness in patients with neuromuscular disorders and gait abnormalities. Even though there are several tools available to quantify ambulatory behavior in a home environment, reliable measurement of joint motion is still limited to laboratory(More)
The annotation of human activity is a crucial prerequisite for applying methods of supervised machine learning. It is typically either obtained by live annotation by the participant or by video log analysis afterwards. Both methods, however, suffer from disadvantages when applied in dementia related nursing homes. On the one hand, people suffering from(More)