Classification of Sleep Patterns by Means of Markov Modeling and Correspondence Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Baby-Posture Classification from Pressure-Sensor Data
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
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The monitoring of sleep patterns is of major importance for various reason such as, the detection and treatment of sleep disorders, the assessment of the effect of different medical conditions or medications on the sleep quality and the assessment of mortality risks associated with sleeping patterns in adults and children. Sleep monitoring by itself is a difficult problem due to both privacy and technical considerations. The proposed system uses a bed pressure mat to assess and report sleep patterns. To evaluate our system we used real data collected in Heracleia Lab's assistive living apartment. Our method is non-invasive, as it does not disrupt the user's usual sleeping behavior and it can be used both at the clinic and at home with minimal cost.