Abstract
We report on first results of using motion pattern behaviour as a possible diagnostics marker for detection and prediction of alzheimer diseases. We observed elderly subjects with and without dementia and recorded their motion behaviour with mobile sensors for 3 days. Additionally, we analyzed the sensor data offline and used probabilistic models (Hierarchical Hidden Markov Models) to differentiate between healthy subjects and subjects suffering form the disease. Our first results with 32 subjects achieve an accuracy of 91 percent.
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Hoffmeyer, A., Yordanova, K., Teipel, S., Kirste, T. (2012). Sensor Based Monitoring for People with Dementia: Searching for Movement Markers in Alzheimer’s Disease for a Early Diagnostic. In: Wichert, R., Van Laerhoven, K., Gelissen, J. (eds) Constructing Ambient Intelligence. AmI 2011. Communications in Computer and Information Science, vol 277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31479-7_21
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DOI: https://doi.org/10.1007/978-3-642-31479-7_21
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