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