Title :
Split-merge algorithm and Gaussian mixture models for AAL
Author :
Yin, GuoQing ; Bruckner, Dietmar
Author_Institution :
Inst. of Comput. Technol., Vienna Univ. of Technol., Vienna, Austria
Abstract :
Analyzing time series sensor data and build statistical model in real time has to overcome two problems at least: the data count increase with time and the distribution of the data is dynamically. To deal with this kind of problems Gaussian mixture model and split-merge algorithm provide useful way. In an AAL project we handle the time series sensor data from a medical box contactor and a meal entrance contactor. Using Gaussian mixture model and split-merge algorithm to analyze the sensor data gathered for about one and a half months and built the statistical model.
Keywords :
Gaussian processes; handicapped aids; health care; intelligent sensors; learning (artificial intelligence); statistical analysis; time series; AAL; Gaussian mixture models; data count increase; data distribution; meal entrance contactor; medical box contactor; self-splitting Gaussian mixture learning; split-merge algorithm; statistical model; time series sensor data; Algorithm design and analysis; Analytical models; Clustering algorithms; Data models; Heuristic algorithms; Senior citizens; Signal processing algorithms; Gaussian Mixture Models; Real Time Analysis; Split-Merge Algorithm;
Conference_Titel :
Industrial Electronics (ISIE), 2010 IEEE International Symposium on
Conference_Location :
Bari
Print_ISBN :
978-1-4244-6390-9
DOI :
10.1109/ISIE.2010.5637774