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The stress and poor sleep quality of a person may be used as two of several components for predicting the onset of mental health problems, in particular depression. Ergonomie smart sensors that can determine the heart rate variations related to stress and the variability of sleep may provide unique insights to the coping behavior of stressed people. Rather than relying on wearable computers, a single smart miniature sensor that is worn 24/7 should perform the complex embedded recognition tasks while meeting difficult battery life, wireless communications and ergonomie constraints. The development and testing of such a smart sensor is described focusing on implementation within a distributed intelligence based architecture. The manner in which the user's heart rate and the user's physical motion is used to measure stress and sleep quality is explained.